{ "schema_version": "1.0", "updated": "2026-08-15", "entity": { "name": "DeCue Technologies", "category": [ "voice privacy", "signal processing" ] }, "team": { "section_title": "Who We Are", "revision": "r300 with r342 native-stack flow", "source": "Member-specific authoritative sources recorded with each biography", "source_retrieved": "2026-08-04", "layout": "One semantic page keeps all three compact leadership profiles visible together in equal desktop columns. A clearly labeled button on each card opens that founder's complete biography in one shared native dialog modeled on Section 01's A, B, and C detail-screen grammar. The dialog scrolls independently, contains boundary wheel and touch input, closes by button, Escape, or backdrop, and returns focus without moving the underlying page. Below the leadership cards, Contact Us provides the general address info@decuetech.com and an accessible service-updates dialog. At r300, that dialog posts the visitor's email address and explicit consent through the existing public request endpoint using a distinct service_updates request type. The site maps the request to the endpoint's legacy required contact fields with fixed service-update labels; the API stores the request and sends an SES notice to info@decuetech.com without opening the visitor's email application. Small screens stack the three compact cards and retain both dialogs.", "general_contact": "info@decuetech.com", "service_updates": "The visitor provides only an email address and explicit consent. The site maps that submission to the public endpoint's legacy required contact fields with fixed service-update labels, including role other and request_type service_updates; the API stores the request and sends an SES notice to info@decuetech.com. It does not open the visitor's email application or claim automatic list enrollment.", "members": [ { "name": "James Palczynski", "title": "Co-Founder & Chief Executive Officer", "email": "jp@decuetech.com", "bio_source": "Biography supplied by James Palczynski on 2026-08-04", "bio": "James grew up on the sell-side as part of an II-ranked equity research team at Smith Barney. He was recruited to initiate a multi-sector demographic coverage universe, doing so under the “YouthQuake” banner until he departed Needham & Co. as senior analyst in 2000 to become an early partner at ICR, where he helped to develop and proliferate a new IR service paradigm. ICR evolved IR from an administrative function into an important strategic advisory role, underpinned by institutional capital markets expertise and experience. This vision of IR has come to dominate both internal and agency conceptions of the role. James remained a partner at ICR for almost two decades as it became the largest independent IR advisory in the United States. He has advised public company management teams across several verticals on disclosures for every type of communication, including for ongoing results, primary and secondary transactions, crisis situations, activist defense, and mergers and acquisitions. In 2025, after reading an article titled “Silent Suffering” in the Journal of Accounting Research that identified non-consenting CEOs with major depression, he has dedicated all of his efforts to developing DeCue to protect public executives and the issuers they serve from invasive voice analysis." }, { "name": "Prof. Dana Carney", "title": "Co-Founder & Chief Scientific Officer", "email": "dc@decuetech.com", "bio_source": "Official biography by Dana R. Carney, published by Berkeley Haas at https://haas.berkeley.edu/faculty/dana-r-carney/, retrieved 2026-08-04", "bio": "Dana R. Carney is a professor at Berkeley Haas and holds the George Quist Chair in Business Administration. She is an affiliate of the UC Berkeley Department of Psychology, director of the Institute of Personality and Social Research (IPSR), and a Barbara and Gerson Bakar Faculty Fellow. Carney studies social behavior, and she is particularly interested in the behavioral expression of prejudice, political affiliation and engagement, generosity, power, and status. Her work often dives deeply into the most micro aspects of social behavior—nonverbal behavior—and much of her work seeks to uncover what it is we actually do with our bodies and faces when we express prejudice, or status, for example. She has been invited to share her research and teaching at academic conferences, universities, and companies all over the world. To Wall Street, she often instructs on topics related to power, status, corruption, and deception. To biotech, pharma, and tech she instructs on topics related to subtle forms of prejudice and discrimination, teamwork, culture, power, and nonverbal communication. At the National Labs, she instructs on teamwork, diversity, and social networks. Prior to Berkeley, Carney was an assistant professor of Management at Columbia University’s Graduate School of Business. She has served as Faculty Director for Women in Technology at Berkeley Executive Education. Carney teaches undergraduates and MBA and Ph.D. students at Berkeley Haas and in the Psychology Department. She has published over 50 research articles, many of which are highly cited and visible in the media and in popular books. In 2011 she received the National Science Foundation’s CAREER award in Social Psychology and in 2010 the Rising Star award from the Association for Psychological Science. Carney received her PhD in social psychology from Northeastern University in 2005 and was a postdoctoral fellow in the Department of Psychology at Harvard University until 2008." }, { "name": "Seth O'Neal", "title": "Co-Founder & Chief Technology Officer", "email": "so@decuetech.com", "bio_source": "Biography supplied by Seth O'Neal on 2026-08-05", "bio": "Seth's career spans more than three decades of enterprise software and systems experience, with deep expertise in secure cloud computing and the handling of highly sensitive data. He began in the airline industry, developing reservation-system software for American Airlines and the SABRE Group, before moving into two decades of building mission-critical systems for healthcare, financial, and utility organizations.\n\nHe has led engineering teams as both an independent consultant and a corporate lead developer, designing systems ranging from automated business-rules and character-recognition platforms to EDI-based healthcare billing and claims systems handling protected health information. That work included founding and running his own consulting practice, auditing and rebuilding business-critical systems for clients before returning to enterprise healthcare technology.\n\nAt Change Healthcare, Seth helped design and build a pharmacy benefits platform on AWS using a micro-services architecture that processes millions of prescription claim transactions daily, and later led its modernization to cloud-native infrastructure. At Optum's Dental Network, he led on-shore and off-shore engineering teams through the migration of legacy systems to secure, container-based AWS environments, establishing development and testing best practices along the way — the same rigor around protecting confidential records that he brings to DeCue as Chief Technology Officer." } ] }, "faq_content": { "revision": "r305", "source": "prototypes/website-v2/SECTION_06_FAQ_WORKING_REFERENCE.md; that reference records the original DOCX provenance, which is not present in this checkout", "source_instruction": "James directed inclusion of all three FAQ TODO items in the current review build on 2026-08-09. The investor-objection question is first, the anti-AI question is second, and the executive-health answer is replaced. This remains review copy; securities counsel review is required before production publication.", "question_count": 29, "category_count": 10, "numbering_note": "The current review contains 29 sequential question-and-answer entries. The public interface preserves that order and presents them as 01 through 29.", "evidence_note": "The health answer uses 'Researchers' and 'several published studies' because the available primary paper identifies two authors and the local timeline does not support the draft's student-team or roughly-a-dozen formulations.", "safe_harbor_addition": "The final answer includes the exact recommended disclosure from the canonical #why-it-matters section.", "categories": [ { "title": "Most Commonly Asked Questions", "questions": [ { "source_number": 1, "question": "Aren't you helping executives hide information from investors?", "answer_blocks": [ { "type": "paragraph", "text": "No. DeCue blocks no information of any kind that an investor typically does, in our view certainly should, and historically always has had access to on a quarterly call. Every word spoken, every meaning conveyed, and every audibly perceivable quality of the speaker's delivery is preserved exactly. Everything a human listener has ever received from an earnings call — in the room, on the line, or in the replay — passes through DeCue untouched. Rigorous analysis of that record is what markets are for. What we disrupt is something different: a machine-only layer of involuntary signal that the speaker did not choose to transmit, cannot perceive, and cannot control." }, { "type": "paragraph", "text": "Consider what the operators of these systems actually seek. If anyone on a public call asked management to discuss their emotional state, their private health conditions, or whether their confidence on a particular topic was genuine, no management team we know would dignify the question with an answer — and not a person in the room or on the call would find that refusal improper. Those withheld answers are precisely what these systems extract: without the speaker's consent, without any disclosure that it is happening, in secret, to gain an advantage over the rest of the market through informational asymmetry. That asymmetry is created entirely by the operators of these systems — through no act or fault of the issuer." }, { "type": "paragraph", "text": "To our knowledge, none of this is illegal today. We find it unethical all the same, and contrary to the spirit of decades of securities regulation built on a simple principle: all investors should have access to the same information, at the same time, through official channels, to make their investment decisions." }, { "type": "paragraph", "text": "That is what DeCue protects. We defend a privacy interest that every one of us would claim for ourselves, and we ensure that markets act on the information issuers intentionally provide. We take issue with the idea that any investor should feel entitled to information that can only be extracted from a speaker by a superhuman capability — information the speaker never knew they were giving." } ] }, { "source_number": 2, "question": "Is DeCue anti-AI?", "answer_blocks": [ { "type": "paragraph", "text": "No — closer to the opposite. The capabilities we defend against are not a defect of AI; they are among its most valuable traits. A machine that can hear stress, fatigue, or distress in a voice can interact with people far better than one that cannot, and the consent-based applications of that perception — patient monitoring, safer systems, genuinely responsive interfaces — are important and welcome. We would consider it a real loss if these capabilities were banned or degraded. DeCue does not restrict what AI systems can perceive; it restricts what one narrow category of audio makes available to be perceived, at the speaker's choice." }, { "type": "paragraph", "text": "The problem is not the perceiver. It is the operator who points that perception at non-consenting speakers, in secret, to extract private information and trade on the asymmetry. In that scheme the AI is an instrument, not an author — an unwitting party to an exploitation it did not choose. Humans have always perceived one another's voices; what governs us is consent and context. Machine perception arrived at superhuman sensitivity with no governance attached, and in public, recorded speech there is only one place governance can attach: the signal itself, under the speaker's control, before the audio leaves their hands." }, { "type": "paragraph", "text": "That is what DeCue is — not a blindfold for AI, but a consent layer for speakers. It lets an executive choose the contexts in which their involuntary vocal layer is readable, rather than choosing between total legibility to every system on earth and not speaking at all. And candidly: we believe unchecked covert exploitation is the fastest route to a backlash that would damage machine perception's legitimate uses along with its predatory ones. The best future for voice AI and the best future for the people it listens to are the same future — one where rich perception and meaningful consent coexist. DeCue exists to keep that future available." } ] }, { "source_number": 3, "question": "How do you know executive voice is being captured and analyzed?", "answer_blocks": [ { "type": "paragraph", "text": "First, there are several third-party vendors who advertise this capability, particularly the extraction of voice signals from below the threshold of human perception. Two particularly visible vendors, who self-describe those capabilities, are Markets EQ and Speech Craft Analytics. Markets EQ is included as an “alternative data provider” on both the Bloomberg and FactSet platforms while Speech Craft, an experienced “sentiment analysis” provider, pursues a direct-to-customer distribution strategy." }, { "type": "paragraph", "text": "Second, there are published academic papers that read like instruction manuals for assembling a cutting-edge voice analysis system. In general, the peer-reviewed literature on this topic is well-established with roots that show decades of replication success. While the corpus of literature accelerated dramatically following the convergence of necessary technologies in 2022, it had expanded steadily prior to that time. The most recent paper in our timeline, published by the University of Chicago Booth’s Journal of Accounting Research, claims a 3.87% excess return on a model portfolio that employs their system’s capabilities. We believe that if an excess return anywhere near that number is achievable, there would be a crowd of portfolio managers wanting such a system. Indeed, there have been over 50,000 downloads for the code associated with that paper on Hugging Face.", "primary_sources": [ "https://doi.org/10.1111/1475-679X.70015", "https://huggingface.co/waiv/FinVoc2Vec" ] }, { "type": "paragraph", "text": "The third reason we have no doubt this is a widely deployed capability is because of the numerous press articles, media interviews and other materials in which these capabilities are discussed at varying levels of detail. We have trouble explaining why there has not been a public outcry or why awareness of the technology is somehow still low, despite these many articles. That said, it is of note that these systems are, by their nature, operated in complete secrecy. We also can think of no advantage to be gained by operators of proprietary systems or customers of a vendor to disclose use of this capability." } ] }, { "source_number": 4, "question": "How do you know that the executive health information has been compromised?", "answer_blocks": [ { "type": "paragraph", "text": "Part of this we know with certainty, because it was published. Researchers built a system that analyzed the earnings-call voices of public-company executives and identified, without their knowledge or consent, which of them showed vocal markers of depression. That work appeared in the Journal of Accounting Research, and it is not an outlier: it is one of several published studies extracting involuntary signal from executive conference-call audio, several of which appear in the research timeline on this page. To the researchers' credit, this work was done in the open, which is exactly why it is visible. So the question is not whether such systems exist. They verifiably do. They work. And the people who built them told the world how.", "primary_source": "https://onlinelibrary.wiley.com/doi/10.1111/1475-679X.12590" } ] }, { "source_number": 5, "question": "How is this any different from NLP-based sentiment analysis?", "answer_blocks": [ { "type": "paragraph", "text": "The core difference is that NLP-based systems examined the textual content of disclosures. The adversaries we are concerned with extract and utilize disclosure content that was produced unintentionally, information that speakers themselves are unaware they have provided. This information in voice, at the sub-perceptual level, reflects the contents of the speaker’s subconscious mind, beliefs that may not even have yet risen to the level where the speaker has introspective access to them." }, { "type": "paragraph", "text": "If investors requested this kind of information be made public, we believe those requests would be denied and dismissed out of hand. No public executive we know would consent to investor demands for regular polygraph exams or mental and physical health screening where the results of those tests would be made public. This new voice capability is akin to both, and can be operated not only without consent, but without even the subject’s awareness. These data are extracted, utilized selectively and without disclosure. We think that puts these new voice systems in a very different category than any previously known analytical tool or technique." } ] }, { "source_number": 6, "question": "Since this is relatively new technology and it may prove inaccurate, isn’t concern about the use of it premature?", "answer_blocks": [ { "type": "paragraph", "text": "Not at all. First, we believe the vendors in this space are highly likely to be capable of providing precisely what they claim to be able to provide. It is important to understand that this is not “new technology.” While the capability itself is newly available on consumer hardware, the understanding of the data, the analytical methodology, and many of the associated methods have existed for a long time. It is more accurate to think of voice technology not as new, but instead as newly practical or newly accessible." }, { "type": "paragraph", "text": "The scientific basis of this capability relies on findings that are well-established and tested through replication. The extraction of voice-based cues by machine is also a technology that goes back many years. Voice analysis requires both the extraction of sub-perceptual cues and the tagging or “coding” of those cues. Until 2022, that cue coding was a laborious, manual process done in scientific labs mostly by graduate students. This could take days to process a single call. The same was generally true for transcription, which was, for a very long time, notoriously unreliable and required a manual review by a transcriptionist. Machine-learning-enabled AI systems such as Whisper and TRILLsson, both released in 2022, ushered in a completely new era in voice technology." }, { "type": "paragraph", "text": "Additionally, if we were to partially concede the point, we would agree that there are likely to be some systems (particularly proprietary or amateur-built systems) that do not properly extract, code or attribute voice cues. That does not mean that investors operating those systems will recognize they are inaccurate or that they will not utilize the incorrect information they develop. Accurate or inaccurate, if investors are communicating or trading on the information, this means, necessarily, that an issuer’s intentional disclosure has been discounted in its importance in favor of alternative information. That is a loss of control and input by the issuer into the issuer’s own enterprise valuation." } ] }, { "source_number": 7, "question": "Our team regularly receives presentation training on controlling our delivery and speaking with intent, so shouldn’t I be less concerned about this as a result?", "answer_blocks": [ { "type": "paragraph", "text": "No, these are signals that you did not choose to make, are not aware you are making, and can’t prevent in your own voice. These are signals produced by autonomic processes that are beyond your ability to control or recognize. They are not something anyone can hear as they are only extractable with digital signal processing techniques. It is important to understand that this new voice technology is a superhuman capability. At the same time, given our experience, we are supportive of presentation training for a variety of reasons. Among those reasons is that there are some measures of voice analysis (like Vocal Delivery Quality, VDQ) that measure perceivable paralinguistic content. Presentation training may improve those types of measures." }, { "type": "paragraph", "text": "It is only through denial of the sub-perceptual cues in voice that you can frustrate these adversarial systems." } ] }, { "source_number": 8, "question": "Since you are changing things that no one can hear and since your system leaves the voice that we hear unchanged, how do you know and how do we know that your system actually works?", "answer_blocks": [ { "type": "paragraph", "text": "We are happy to disclose, for potential customers, precisely how our system works, and we will share the validation information we collect to demonstrate our system’s effectiveness. What we’ve built over the past year is a very sophisticated digital signal processing system that operates on voice exclusively below the threshold of human perception. We are confident and can demonstrate that we destroy the fidelity of sub-perceptual signal in voice." }, { "type": "paragraph", "text": "Every operation and process used by the DeCue system is based on extensive peer-reviewed scientific findings. We utilize science from nearly a dozen different, related literatures to ensure that our system achieves two equally important objectives. The first is to disrupt the sub-perceptual voice signals that we find so concerning. The second is to preserve the natural, intentional cues in voice that generate meaning." } ] }, { "source_number": 9, "question": "Since your system only addresses pre-recorded audio, aren’t I still exposed to the analysis of the content in my Q&A session?", "answer_blocks": [ { "type": "paragraph", "text": "We degrade a system’s ability to collect useful sub-perceptual information from Q&A even though we don’t directly disrupt signals in that portion of the call. Our removal of the typically very clear sub-perceptual cues from prepared remarks prevents an adversarial system from extracting a clean baseline understanding of each speaker’s voice." }, { "type": "paragraph", "text": "Contrary to the common belief that Q&A is the richer source of unintentional speaker information, prepared remarks are a much more vulnerable portion of the call for voice analysis systems to penetrate. Prepared remarks feature lengthy, uninterrupted, measured delivery in a high-quality recording environment. This is a nearly perfect environment to source data for a voice-analysis process. It enables a system to both establish a speaker baseline and to extract significant amounts of unintentional disclosure on a full range of subject material from an executive’s voice." }, { "type": "paragraph", "text": "Q&A, by contrast, is more likely to contain a higher incidence of human-perceivable vocal cues, to be more difficult to analyze due to interruptions and diarization challenges, to have higher levels of background noise, and to contain voice content that lacks the length of commentary that enables the establishment of a useful vocal-performance baseline for any given speaker." }, { "type": "paragraph", "text": "We are certainly working on a streaming capability, but there is significant processing required for scrubbing voice of its sub-perceptual information. The latency this process would introduce into streaming voice is simply too high to be useful for streaming audio." } ] } ] }, { "title": "The Threat", "questions": [ { "source_number": 10, "question": "What is paralinguistic extraction?", "answer_blocks": [ { "type": "paragraph", "text": "This refers to the measurement of certain features of the qualities inherent in voice, typically derivative or compound measures of pitch, intensity and pace that provide information related to meaning. Listeners tend to perceive paralinguistics at a level the speaker intends (with pronounced paralinguistic values). Paralinguistic information produced at an automatic level can be extracted from digital voice files, revealing the state of a speaker's mental and physical condition." } ] }, { "source_number": 11, "question": "How widespread is this threat?", "answer_blocks": [ { "type": "paragraph", "text": "Paralinguistic analysis of earnings calls has become, to the best of our knowledge, an increasingly common practice on the institutional buy side. It remains an active and growing field of academic research. Published studies have demonstrated correlations between certain voice measures and excess portfolio returns, as well as the ability to detect various health conditions, emotional states, indications of deception, and other characteristics from earnings-call audio. With over 50,000 earnings calls available as an API-ready dataset and AI models like Google TRILLsson and OpenAI Whisper making extraction and feature coding increasingly accessible, the threat is both real and accelerating." } ] } ] }, { "title": "Product", "questions": [ { "source_number": 12, "question": "Can listeners tell the audio has been processed?", "answer_blocks": [ { "type": "paragraph", "text": "No. The DeCue system restricts its modifications to a rich layer of fine signal in a voice that does not reach the threshold of human perception. Only digital voice processing systems can read voice at this level of sensitivity." } ] }, { "source_number": 13, "question": "Does DeCue change what the executive is saying?", "answer_blocks": [ { "type": "paragraph", "text": "No. The DeCue system does not change either what an executive says or the way in which those words are heard by any human listener. We change the information in a voice that, while it contains significant information, is typically only accessible by examining digital audio files and is only readily interpretable with the use of machine-learning-enabled voice systems." } ] } ] }, { "title": "Security", "questions": [ { "source_number": 14, "question": "How secure is my audio?", "answer_blocks": [ { "type": "paragraph", "text": "Extremely secure. Your audio is encrypted both in transit and at rest using AES-256 encryption, and stored in a fully private AWS environment — there is no public internet path to your files at any stage of processing. Only automated systems can access your audio; no individual at DeCue can reach it unilaterally, and accessing the raw audio environment requires authorization from more than one DeCue principal. We retain original audio for 72 hours and do not store voice files or speaker profiles beyond that window." } ] }, { "source_number": 15, "question": "Who at DeCue can access my recordings?", "answer_blocks": [ { "type": "paragraph", "text": "No one can access your recordings unless you specifically authorize us to do so. While our system does contain information about the contents of your audio conference call, those files are not reviewed by or available to any person at DeCue unless specifically directed to do so by you. We do not need to know the content of a call to verify the proper functioning of our system or to confirm your audio files have been protected. 100 percent confidential. Metadata only. No content availability." } ] }, { "source_number": 16, "question": "Is DeCue SOC 2 compliant?", "answer_blocks": [ { "type": "paragraph", "text": "DeCue is currently in a SOC 2 compliance review process. This is a present-status description only and is not a claim of SOC 2 certification." } ] } ] }, { "title": "Technical", "questions": [ { "source_number": 17, "question": "What audio formats are supported?", "answer_blocks": [ { "type": "paragraph", "text": "DeCue accepts all standard professional audio formats, including WAV, MP3, FLAC, and AAC. Your conference call provider's native output format is supported. If you have questions about a specific format, contact us." } ] }, { "source_number": 18, "question": "What is the processing time?", "answer_blocks": [ { "type": "paragraph", "text": "DeCue processes prepared remarks and returns protected audio files within hours of submission, well within the standard earnings call preparation timeline. Exact turnaround depends on file length and queue, but same-business-day delivery is our standard commitment." } ] } ] }, { "title": "The Science", "questions": [ { "source_number": 19, "question": "What are eGeMAPS features?", "answer_blocks": [ { "type": "paragraph", "text": "eGeMAPS (extended Geneva Minimalistic Acoustic Parameter Set) is a standardized set of 88 acoustic parameters widely used in computational paralinguistics research. These include measures of pitch, loudness, spectral energy, and voice quality that machine-learning systems use to infer emotional state, health markers, and cognitive load from voice. DeCue targets all 88 eGeMAPS features." } ] }, { "source_number": 20, "question": "What does \"sub-perceptual\" mean?", "answer_blocks": [ { "type": "paragraph", "text": "DeCue's modifications operate below the threshold of human perception — meaning no human listener can detect that the audio has been processed. The voice sounds identical in every way that matters to human hearing while being fundamentally corrupted for machine analysis." } ] }, { "source_number": 21, "question": "Is this based on peer-reviewed science?", "answer_blocks": [ { "type": "paragraph", "text": "Yes. DeCue's approach is built on established research across ten scientific disciplines, including linguistics, computational paralinguistics, perception studies, clinical psychology, affective computing, and machine learning." } ] } ] }, { "title": "Integration", "questions": [ { "source_number": 22, "question": "How does this fit into our existing earnings call workflow?", "answer_blocks": [ { "type": "paragraph", "text": "DeCue integrates into the final stage of your prepared remarks process. After your management team has finalized and recorded their prepared remarks, the audio is uploaded through your secure DeCue portal. Protected audio is returned for use with your conference call provider. The workflow adds one step — it does not change how you prepare, rehearse, or deliver your call." } ] }, { "source_number": 23, "question": "Which conference call providers are supported?", "answer_blocks": [ { "type": "paragraph", "text": "DeCue works with all major earnings call providers, including Notified (formerly PGi), Chorus Call, Q4, West, and others. We deliver a protected audio file in your provider's required format. If your provider isn't listed, contact us — if they accept audio files, we can support them." } ] } ] }, { "title": "Competitive", "questions": [ { "source_number": 24, "question": "Who else does this?", "answer_blocks": [ { "type": "paragraph", "text": "No one. DeCue is the first and only system specifically designed to neutralize AI-extractable paralinguistic signals from executive voice while preserving the audio's perceptual quality. Voice encryption makes audio unintelligible; voice alteration changes how a speaker sounds. DeCue does neither. It corrupts the sub-perceptual data layer that machine-learning systems exploit while leaving the voice indistinguishable to every human listener." } ] }, { "source_number": 25, "question": "How is this different from voice encryption?", "answer_blocks": [ { "type": "paragraph", "text": "Voice encryption makes audio unlistenable without a decryption key — it's designed for secure transmission. DeCue's purpose is fundamentally different: the protected audio is meant to be heard publicly, broadcast on your earnings call, and filed with the SEC. It sounds identical to unprotected audio. The difference is invisible to humans and devastating to AI extraction systems." } ] } ] }, { "title": "Results", "questions": [ { "source_number": 26, "question": "How do we know it worked?", "answer_blocks": [ { "type": "paragraph", "text": "Every processed file is delivered with a Protection Report — a detailed breakdown of the modifications applied across all 88 eGeMAPS features and MFCC layers 1–14. The report confirms that modifications were applied, that they fall below the threshold of human perception, and that the protected file is forensically reproducible from its deterministic seed." } ] }, { "source_number": 27, "question": "What's in the Protection Report?", "answer_blocks": [ { "type": "paragraph", "text": "The Protection Report is focused on disruption metrics, before/after analysis summaries, and a confirmation that all modifications fall within sub-perceptual parameters. It does not contain a transcript of the call. It provides everything you need to verify protection without exposing the content of your remarks." } ] } ] }, { "title": "Legal & Compliance", "questions": [ { "source_number": 28, "question": "Can we use DeCue'd audio for SEC filings?", "answer_blocks": [ { "type": "paragraph", "text": "Yes. DeCue does not alter the words spoken, the meaning conveyed, or the audible quality of the recording. The protected audio is a faithful representation of what was said, suitable for any regulatory filing that accepts audio of prepared remarks. Consult your legal counsel for your specific filing requirements." } ] }, { "source_number": 29, "question": "Does this affect our Safe Harbor protections?", "answer_blocks": [ { "type": "paragraph", "text": "DeCue strongly recommends that you add a short statement to your Safe Harbor provisions clarifying that sub-perceptual voice signals in the audio broadcast of your call have been modified to protect against the provision of unintended information and protect against the extraction of private personal health information. Please consult your securities counsel (or ask to speak with ours) to decide on the right specific language for your quarterly disclosures. We have provided suggested language:" }, { "type": "quote", "text": "“Listeners are cautioned that today’s call has been protected by advanced signal-processing techniques that do not change the presenters’ voices as perceived by the human ear but corrupt sub-perceptual paralinguistic data contained in those voices—data that are private to today’s presenters and neither intended nor appropriate for public disclosure.”" } ] } ] } ] }, "core_problem": { "summary": "Human speech carries intended semantic content and involuntary paralinguistic data.", "payloads": [ { "name": "intended payload", "visual": "blue carrier", "description": "Language, argument, disclosure, and intended meaning." }, { "name": "autonomic payload", "visual": "orange signal embedded inside blue", "description": "Involuntary acoustic and paralinguistic information carried beside the words, including machine-readable variation below conscious perception." } ] }, "product_intent": "Corrupt sub-perceptual, machine-readable paralinguistic data while preserving the human-perceived voice.", "native_stack_review": { "revision": "r358", "publication_status": "Prepared locally for DEV review; not yet committed, pushed, CI-passed, or deployed. The currently served dev.decuetech.com revision remains r340-hero-half-gap until explicit publication. Not production-approved or production-deployed.", "site_consistency_contract": "The current DEV review enforces a literal 11pt floor for live semantic text in closed and open states, full-width hero lines, 1px structural lines outside purposeful four-sided component outlines, canonical blue underlined interactive text with cyan glow on hover and keyboard focus, visible scrollbars, active navigation reveal, nested-scroll containment, mutually exclusive hardware records, a footer-safe Scientific Literature Timeline with Shift-wheel horizontal movement, and synchronized visible, accessibility, and agent-readable content. The approved original 123-term prepared-remarks cloud is one immutable 1614-by-546 image whose complete pixels may scale proportionally but whose individual words can never reflow or change; its meaning is available through alternative text. The fixed-geometry processing-architecture SVG uses a controlled rendered minimum and observes the literal 11pt floor. On fine-pointer desktop devices, pages are authored at 1920-by-1200 but render viewport-fit: each story plate fills the live window so one complete page is visible at any resolution, including 2560-by-1080.", "section_one": { "plate_count": 2, "interaction": "Ordinary reader-controlled vertical scrolling. No content is assembled by wheel input. The first viewport places three human-heard and protection hero lines above one full-size comparison frame and three AI-operator hero lines below it. A microphone tile on the manual horizontal divider starts at the clean blue carrier and reveals the completed analytical signal suite from left to right without resizing, cropping, redrawing, or changing either waveform's geometry. The visible divider can be grabbed and dragged; the range control also supports keyboard input. A faint cyan instruction glow intensifies on hover or keyboard focus. A, B, and C become operable as their controls enter the revealed field. The second page returns to the clean blue carrier beneath the disclosure-boundary close.", "sequence": [ "This simple sound wave is what voice looks like to the human ear... but there is a deep layer no one can hear, full of psychological and physiological data. DeCue ensures that unheard layer remains unavailable, including to AI voice systems.", "Operators of AI voice systems measure stress, anxiety, and confidence: per word, phrase, and section. They use data patterns in voice to accurately diagnose mental and physical health conditions. Unintentional, unavoidable disclosure about the executives on the quarterly call is extracted and monetized.", "Investors have acquired a superhuman, machine-driven capability. They trade on information no one should hear or know. You chose your words. Now draw the line. DeCue your call." ], "claim_boundary": "The statements that AI voice-system operators use voice-data patterns to accurately diagnose mental and physical health conditions, extract executive information to monetize unintentional unavoidable disclosure, and trade on information no one should hear or know are exact user-directed review copy requiring scientific substantiation, commercial substantiation, and legal review before production. The site's standing evidence boundary remains that published research classification results are not equivalent to validated stand-alone clinical diagnosis." }, "section_two": { "plate_count": 4, "combined_democratization_sequence": [ "Machine learning solved accurate transcription and voice-cue tagging in 2022.", "Google TRILLsson and OpenAI Whisper democratized access to advanced voice.", "Advanced voice capability has become easy to acquire, deploy, and operate on consumer hardware." ], "combined_democratization_visual": "The Advanced Voice System 1995, 2010, and 2022 room-workstation-laptop evidence remains the primary visual. Two compact release tiles are attached to the 2022 laptop: Google TRILLsson dated March 3, 2022 and OpenAI Whisper dated September 21, 2022. Hover, keyboard focus, or click exposes the retained release evidence and authoritative external source link. The former standalone Google/OpenAI page and its six application bullets are absent.", "domino_cover_sequence": [ "The science of voice has developed broadly and steadily, but application was challenging.", "Hardware improved, but transcription and expertise remained blockers.", "Those barriers fell in 2H22 as one of the first real AI-transformer breakthroughs.", "Decades of overpromise and underdeliver gave way to extremely capable voice systems.", "Advanced voice in the home, cars and many businesses is now common.", "As are unintended consequences... deep fakes and voice cloning scams.", "The most dangerous misuse has escaped notice... analytic surveillance." ], "domino_visual_boundary": "The authoritative domino image, deterministic crop, chain labels, and terminal label remain unchanged. Horizontal rules above and below the image, the detached capability box, and its arrow are absent. The image is centered at the largest size the one-page composition permits; the four statements below describe capable systems, advanced voice becoming common, unintended deep-fake and voice-cloning consequences, and analytic surveillance as the most dangerous unnoticed misuse. All seven hero statements share one size, with a fifteen-percent increase only on canvases wide enough to keep every statement on one line.", "companies_plate": "The third plate presents the incentives and opportunity created by newly accessible voice capabilities through the six-company field. Each company retains its pointer, keyboard-focus, and tap-accessible funding or transaction overlay, including explicit no-public-Series and acquisition boundaries where applicable.", "final_plate": "The 89-record Scientific Literature Timeline remains the fourth and final Section 02 plate and spans 1981 through 2026. The submenu labels map to A VOICE TECHNOLOGY CONVERGENCE, B DEMOCRATIZATION OF VOICE, C INCENTIVES AND OPPORTUNITY, and D SCIENTIFIC LITERATURE TIMELINE." }, "section_three": { "plate_count": 3, "sequence": [ "Voice technology was incorporated into sentiment analysis over the supplied CEO image.", "The original text-NLP collage explains the earlier scoring of media mentions, adjective use, and sentence length.", "The completed indicator suite and attributed Speech Craft Analytics and Markets EQ evidence present the unseen attack." ], "boundary": "The six-company opportunity and funding material appears only in Section 02. Section 03 uses three complete reader-controlled pages; no standalone company or funding page remains here." }, "section_four": { "plate_count": 3, "sequence": [ "The counsel-reviewed Silent Suffering origin frame combines the enlarged linked Journal of Accounting Research cover, the roomier deterministic processing-architecture vector, and the three defense-and-preservation statements. The former eavesdropping drawing is absent.", "The registered cyan carrier and orange inner payload show the sub-perceptual signal disrupted at the filter.", "The exact Safe Harbor recommendation and disclosure accompany the secure AWS deployment, immediate processing, and two-hour secure-return statements. The former voice-vault image is absent." ], "boundary": "The Safe Harbor box is integrated into the third What We Built page in the former vault-image slot. No standalone Safe Harbor page follows, eliminating one complete page without duplicating or rewriting its disclosure." }, "section_five": { "page_count": 1, "summary": "One Who We Are page presents James Palczynski, Prof. Dana Carney, and Seth O'Neal together. Each View Biography control opens the shared accessible founder dialog, and the Contact Us area includes the consent-based service-updates dialog." }, "section_six": { "question_count": 29, "category_count": 10, "summary": "The FAQ is a native semantic disclosure list in ordinary document flow. It contains 29 sequential questions in 10 categories and does not use an authored boundary dissolve." }, "section_seven": { "page_count": 1, "summary": "Log In and Create Account hand off to the isolated customer portal; the public page does not collect credentials or process audio. Contact Us opens email to info@decuetech.com." } }, "visual_sequence": [ "Section 01 page one is complete on arrival. Three human-heard and protection statements sit above one full-size comparison frame and three AI-operator statements sit below it. A directly draggable microphone handle and keyboard-operable range input reveal the registered analytical layer from left to right while preserving the waveform geometry. A, B, and C become operable as their controls enter the revealed field.", "Section 01 page two inserts a deliberate blank entry slice above the three disclosure-boundary statements, then returns to the clean blue carrier.", "Section 02 page A presents the seven-line science-to-analytic-surveillance argument with the authoritative domino image and four consequence statements.", "Section 02 page B presents democratization through the Advanced Voice Systems in 1995, 2010, and 2022 plus compact Google TRILLsson and OpenAI Whisper evidence.", "Section 02 page C presents six company opportunity records with accessible funding or transaction disclosures.", "Section 02 page D presents the 89-record Scientific Literature Timeline spanning 1981 through 2026.", "Section 03 page one introduces voice technology's incorporation into sentiment analysis over the supplied CEO image.", "Section 03 page two presents the earlier text-NLP methods through the conceptual media, adjective, and sentence-length graphics.", "Section 03 page three presents the unseen-attack indicator suite and attributed Speech Craft Analytics and Markets EQ evidence.", "Section 04 page one combines the Silent Suffering origin evidence with the defense-and-preservation statements.", "Section 04 page two presents the registered cyan-and-orange filter disruption.", "Section 04 page three presents secure AWS deployment and file return beside the exact Safe Harbor recommendation and disclosure.", "Who We Are, the 29-question FAQ, and Log In / Create Account follow; there is no separate Safe Harbor page.", "Ordinary reader-controlled document scrolling moves through every complete page; wheel input does not assemble timed story states or trigger boundary dissolves." ], "illustration_status": "The waveform, lens instrument overlay, delta-Hz scale, enlarged orange candlestick bodies and shadows, normalized word-stress score, seven-line health template, marker contours, and condition label are conceptual explanatory graphics, not measurements from a real recording, speaker results, clinical diagnoses, deception determinations, or a live product demonstration.", "health_marker_examples": { "labels": [ "Neurodivergence / autism spectrum", "Major depression", "Bipolar disorder", "PTSD", "Generalized anxiety", "Schizophrenia-spectrum conditions", "Parkinson's disease", "Early Alzheimer's / cognitive impairment", "Heart-failure treatment status" ], "meaning": "Conditions discussed inside the opt-in Health Condition Pattern Recognition screen because each has a published speech or voice research literature. Section 01 shows one abstract four-zone pattern using the registered Parkinson's marker geometry and a color-matched yellow-green branching bracket; the first marker stays fixed while the other three populate around it. It is an explanatory example, not a diagnostic result.", "diagnostic_status": "The visible seven-line template and its recurring contours are invented for visual explanation. They are not validated biomarkers, diagnoses, or identification results for any listed condition." }, "section_one_detail_screens": { "menu_label": "01 Protecting Executive Voice", "lock_status": "Locked at revision r181, including A, B, and C, except for James's explicitly named later exceptions through r304. Those exceptions cover the footer labels, cue type, named A/C links, named B/C box removals, opening-primer reset, authored holds, signal-cleanse duration, and analysis-element phases. A/B/C copy, imagery, source waveform geometry, and detail-dialog content remain unchanged. The r342 native-stack exception replaces the historical wheel choreography with two reader-controlled pages and a manual comparison without reopening the detail screens.", "destinations": [ { "key": "A", "title": "Word-Level Scoring", "source_text": "External user-supplied section A text.txt; implemented in the live dialog but not retained in this checkout", "scope": "The screen opens with Word-level scoring distracts from the message by assigning meaning to sub-perceptual signals the speaker never intended to convey. It preserves the standard 40-millisecond analytical-frame and 10-millisecond measurement interval, explains how overlapping frames align audio precisely to timestamps, and describes word-level values for stress and cognitive load derived from variation below conscious perception. The screen states that adversarial systems can attach correlation tags to financial terms and place those keyword findings beside content-agnostic observations about the speaker's emotional and affective state. It restores a wide three-word conceptual stress map whose red spans scale with the illustrated words: 27 registered bars for guidance, 35 for confident, and 45 for competition. Its enlarged caption reads Analysis targets individual words; the sub-perceptual scoring layer reports on the speaker, not the message. The issuer-cost block separates message displacement, narrative re-weighting, and strategic constraint. The investor-intent block separates confidence insight, affective-state identification, and indications of deception. A corrected four-step inference path runs from capture and alignment through feature extraction, a trained classifier or regressor, and calibrated inference. The screen defines the standardized 88-feature eGeMAPS set and MFCC 1-14, including what each is useful for and their originating authorship. The unchanged eGeMAPS and MFCC labels link to James's specified IEEE GeMAPS publication and MFCC reference; the GeMAPS destination is an intentional educational tradeoff rather than a claim that GeMAPS and eGeMAPS are identical. The screen closes by explaining how numerically distinct features can form a dense map of involuntary meaning transmission even when they do not sound different to a listener." }, { "key": "B", "title": "Health Condition Pattern Recognition", "scope": "The screen opens with Mental and physical health conditions can be accurately identified from a speaker's voice alone. Its revised two-paragraph introduction describes voice production as a complex interplay of psychology, neurology, and physiology; explains that adversarial systems can measure artifacts of those processes below the threshold of conscious human perception; and states that scientific literatures report a growing range of conditions that leave a signal in the sub-perceptual layer of variation. It identifies the historical earnings-call corpus as a rich business-school research dataset because past calls can be linked to outcome data, and it criticizes the resulting publication of executive-depression studies in accounting and finance journals rather than medical publications. Immediately above the diagnostic-percentage table, The State of Voice-Cue Science states that the cited literature is not exhaustive, names peer-reviewed research into substance or intoxication effects, sleep deprivation, medication effects, respiratory conditions, and additional voice pathologies, and directs public executives seeking deeper guidance to Chief Scientific Officer Prof. Dana Carney at dc@decuetech.com. The lead evidence grid begins with 85.56 percent asterisked autism-spectrum classification against a mixed non-autistic group, then reports 94 percent heart-failure treatment-status identification, 91.11 percent Parkinson's classification, 89.1 percent PTSD classification, 87 percent pooled depression detection, and 86.2 percent schizophrenia-spectrum classification, with the task and cohort beside every figure. The broader screen covers autism-spectrum neurodivergence first, followed by major depression, bipolar disorder, PTSD, generalized anxiety, schizophrenia-spectrum conditions, Parkinson's disease, early Alzheimer's or cognitive impairment, and heart-failure monitoring. The autism card reports Briend et al.'s asterisked 91 percent child classification against typically developing controls and 85.56 percent against a mixed non-autistic group, keeps the controlled nonword-repetition task and 84-person analyzed cohort attached, and states that no adult cohort was reported. Ordinary adult samples using natural connected speech are the next generalization step; a CEO-specific cohort is not required. The card frames the exposure as non-consensual identification of neurodivergence rather than proof of defect. Every detailed condition card includes a named study, outcome metric, cohort size, evidentiary limitation, and the additional validation required before voice-only diagnosis or identification. The former What diagnosis from voice alone would have to mean box is removed because that phrase does not carry one stable meaning across contexts." }, { "key": "C", "title": "Emotion and Affect Indicators", "source_text": "External user-supplied Section C.docx; implemented in the live dialog but not retained in this checkout", "scope": "The screen opens with Purposeful content available to the human ear should be the only legible channel. It follows the user-authored Section C copy: computational paralinguistics correlates involuntary, including sub-perceptual, acoustic variation with activation, valence, tension, cognitive load, and other affective findings; affect classification maps patterns to estimated labels or dimensions without revealing private thoughts or establishing intent. The issuer-loss block separates message displacement, message credibility, strategic optionality, and reflexive scrutiny, including mistaken attribution from unrelated pre-call events. The feature readout covers pitch, jitter, shimmer, HNR, loudness, spectral balance and flux, harmonic differences, formants, temporal functionals, GeMAPS, and MFCC 1-14. GeMAPS links to James's specified IEEE publication and MFCC links to his specified Wikipedia reference. The former separate Research context box is removed. The deception section describes a directionally consistent cue cluster as a legitimate risk signal that may warrant inquiry while stating that it does not indicate any probability that the speaker engaged in deception and that high-stakes uncertainty and deception can appear very similar under acoustic analysis." } ], "sub_perceptual_model": { "human_experience": "The listener can hear an ordinary, intelligible voice with no consciously meaningful change.", "machine_access": "A system can still measure involuntary acoustic variation, including variation below the human just-noticeable difference, and align those features to words or time windows.", "inference_boundary": "Machine access to sub-perceptual signal is distinct from the validity of the downstream correlation or label. It does not by itself establish health status, emotion, intent, or deception." }, "interaction": "The header item 01 returns the viewport to the current Section 01 opening composition and exposes a dropdown with A, B, and C. Mouse hover opens the dropdown on hover-capable devices; native click, keyboard, and touch behavior remains available. The same screens open from three subject-titled A, B, and C controls inside the manually revealed analytical field. Those controls use a restrained contrast lift, slight upward shift, and directional arrow on hover or keyboard focus instead of generic CLICK FOR MORE text. A sends a slow 9.2-second highlight wave over its fixed gradient without drawing a target box around the waveform. B softly brightens the four yellow-green pattern zones and their 2-pixel bracket, whose #B7EE00 color exactly matches the generated SVG markers. C uses the user-supplied 700-pixel glass.png as a genuine alpha overlay; hover briefly intensifies its curved highlights and then settles without a traveling line. Each screen is a native accessible dialog, scrolls independently, contains wheel input at its top and bottom boundaries so the primary page cannot move underneath it, and returns the visitor to the same scroll position and opening control when closed.", "review_status": "The A/B/C content remains locked at r181 except for James's explicit later copy, link, box-removal, timing, and boundary-containment exceptions through r304. The current r342 native-stack adaptation preserves the registered waveform and complete analytical field but exposes it manually through the pointer-draggable, keyboard-operable comparison instead of the historical wheel-assembled timeline. All A/B/C detail content and dialog behavior remain available.", "issuer_impact": { "A_word_level_scoring": "Regardless of inference accuracy, the practice can dilute investor focus on management's intentional content, assign weight to involuntary acoustic-feature variation that carries no consciously meaningful cue to a listener, allow an inference model to reassign material context, and reduce strategic communications discretion around uncertainty and discretionary disclosure.", "B_health_condition_identification": "Executive privacy leads the consequence set: as voice-analysis capabilities become more commonplace, privacy protection becomes a broader issue, with public executives forming an early population of high-value targets. A diagnostic-level signal for a serious condition could completely displace the investment narrative and compromise privacy and disclosure integrity. No public disclosure of health information captured this way has yet occurred; the stated concern is that such an event could affect disclosure practice across the capital markets, create executive-health or succession speculation, and force a choice between exposing private contingency planning and allowing silence to be misread.", "C_emotion_and_affect_indicators": "Can displace intentional disclosure with inferred emotional state, misattribute unrelated pre-call events to the disclosure, convert strategic nuance into a premature signal of intent, and trigger questions, coverage, or trading attention that seek to price a speaker's emotion at a snapshot in time rather than the quarterly corporate disclosure." }, "adversary_motivation": { "sensitive_personal_information": "Sensitive personal information may represent career or personal disclosure risk to named individuals. The page treats most possible motivations as concerning and emphasizes the alignment of powerful incentives with misuse.", "incentives": [ "influence over employment status", "influence over corporate governance", "creation of a loss of investor or public confidence", "derailment of strategic or operational narratives", "other adverse personal or corporate consequences" ] }, "investor_intent": { "confidence_insight": "An investor focused on granular stress and cognitive-load indicators will presume an ability to estimate an adjusted level of the speaker's certainty about key disclosures, particularly forward-looking statements.", "affective_state_identification": "The investor may use a single word to assign assumed subconscious or suppressed affective and emotional states to the speaker's overall performance, producing a global adjustment that may inform how the face-value messages are adjudicated.", "indications_of_deception": "The investor looks for clusters of paralinguistic cues that might be dismissed individually but, in concert, may signal inaccurate statements, including keywords on which a disclosure's core messages hinge and whose true validity may be available to the speaker only below the level of introspective access." }, "health_information_boundary": "Screen B publishes study-level outcome metrics and cohort sizes to document capability and evidence strength. Sub-perceptual describes machine access to the voice signal, not the strength of a diagnosis. The State of Voice-Cue Science note states that the cited literature is not exhaustive, identifies additional peer-reviewed research areas, and provides Prof. Dana Carney's contact for public executives seeking deeper insights.", "health_evidence_threshold": { "meaning": "The threshold for voice-only diagnosis is an evidence threshold, not an acoustic cutoff.", "required_chain": [ "association", "voice-only classification", "differential and external validation", "stand-alone clinical utility" ], "current_status": "None of the eight listed conditions is presented as having cleared the complete chain for stand-alone voice-only clinical diagnosis or identification.", "depression_citation_boundary": "Liu et al. 2024 reported 87 percent pooled accuracy across eight meta-analyzed speech-depression studies. Cheng and Golshan 2025 trained a measure on 189 clinical interviews and applied it to 14,608 CEO-quarter observations covering 421 CEOs, but CEO clinical ground truth was unavailable. The pooled accuracy must not be attributed to the CEO sample." }, "content_provenance": { "local_copy_sources": [ { "source": "External user-supplied section A text.txt; not retained in this checkout", "used_for": "James's proofed replacement copy for the complete Word-Level Scoring detail screen at revision r176" } ], "public_company_language": [ "https://decuetech.com/", "https://decuetech.com/about", "https://decuetech.com/faq" ], "internal_context": [ { "source_uri": "file:///Users/mindbend/QUIRK/DATA_VAULT/DeCue%20Transfer%20Files/Marketing/Marketing%20-%20Backup/DeCue%20Launch/DeCue%20Launch%20Context/DeCue_Session6_Summary_2026-03-26.docx", "locator": "DOCX paragraphs 1-20 part 1/3", "used_for": "word-level extraction and session-normalization context" }, { "source_uri": "file:///Users/mindbend/QUIRK/DATA_VAULT/DeCue%20Transfer%20Files/Marketing/Various%20Copy/dcEDIT_CEO%20Letter.docx", "locator": "DOCX paragraphs 1-28 part 2/4", "used_for": "risk framing around generated attributions, including inaccurate ones" }, { "source_uri": "file:///Users/mindbend/QUIRK/DATA_VAULT/DeCue%20Scientific%20Library/DeCue_Research_Library_Executive_Summary.pdf", "locator": "PDF pages 4, 6, and 7", "used_for": "deception, health, affect, and cognitive-load evidence boundaries" }, { "source_uri": "file:///Users/mindbend/QUIRK/DATA_VAULT/DeCue_Public%20_Context/02_thought_leadership/Patent_main/Palczynski-001%20Provisional%20-%20ID%20Divergence.docx", "locator": "DOCX paragraphs 28-47 parts 2/12 and 3/12", "used_for": "the seven-condition core list and its internal literature cross-reference" }, { "source_uri": "file:///Users/mindbend/QUIRK/DATA_VAULT/DeCue%20Scientific%20Library/02%20-%20Deception%20Detection/Sporer%20Schwandt%202006%20-%20Paraverbal%20Indicators%20of%20Deception%20Meta-Analysis.pdf", "locator": "PDF page 10 part 2/3", "used_for": "small, heterogeneous cue effects and practitioner caution" } ], "public_research": [ "https://doi.org/10.1109/TAFFC.2015.2457417", "https://doi.org/10.1109/TASSP.1980.1163420", "https://pubmed.ncbi.nlm.nih.gov/34969496/", "https://aclanthology.org/L08-1082/", "https://www.isca-archive.org/interspeech_2018/schuller18_interspeech.html", "https://onlinelibrary.wiley.com/doi/10.1002/acp.1190", "https://www.nationalacademies.org/read/12854/chapter/3", "https://pmc.ncbi.nlm.nih.gov/articles/PMC11413444/", "https://onlinelibrary.wiley.com/doi/full/10.1111/1475-679X.12590", "https://pmc.ncbi.nlm.nih.gov/articles/PMC11254794/", "https://pubmed.ncbi.nlm.nih.gov/31006959/", "https://pmc.ncbi.nlm.nih.gov/articles/PMC9652731/", "https://pubmed.ncbi.nlm.nih.gov/34344490/", "https://www.nature.com/articles/s41398-023-02554-8", "https://www.nature.com/articles/s41598-021-02487-6", "https://pubmed.ncbi.nlm.nih.gov/40188263/", "https://alz-journals.onlinelibrary.wiley.com/doi/abs/10.1002/dad2.12393" ] } }, "capability_collapse": { "statement": "The current Section 02 uses four complete reader-controlled pages: the seven-line science-to-analytic-surveillance domino argument; democratization through Advanced Voice Systems in 1995, 2010, and 2022 with Google TRILLsson and OpenAI Whisper evidence; six company opportunity records; and an 89-source voice-science timeline spanning 1981 through 2026.", "lock_status": "Section 02 remains layout- and choreography-locked except for James's explicit revisions. Four complete reader-controlled plates present the domino argument, democratization evidence, six-company opportunity field, and Scientific Literature Timeline. The authoritative 1586-by-672 domino source and deterministic 1586-by-520 crop remain unchanged. The current domino plate has no horizontal image rules, detached capability list, or arrow; it centers and enlarges the authoritative frame within the available page while dividing the remaining negative space across four zones. The Scientific Literature Timeline redistributes one-fifth of its unused top space beneath the timeline on fine-pointer canvases. Older r280-r342 details are retained below only as historical provenance.", "visual_sequence": [ "Page A presents the unchanged authoritative domino image without horizontal edge rules, a detached capability box, or an arrow. The centered frame is sized to the available page and four statements below describe advanced voice becoming common, unintended deep-fake and voice-cloning consequences, and analytic surveillance as the most dangerous unnoticed misuse.", "Page B compares Advanced Voice Systems in 1995, 2010, and 2022. Google TRILLsson and OpenAI Whisper records attach to the 2022 laptop; only one expandable release record remains open at a time.", "Page C presents six voice-technology companies as evidence of incentives and opportunity. Each company exposes a publicly announced funding or transaction record with explicit source boundaries.", "Page D presents 89 equal-weight voice-related research records from 1981 through 2026 with publisher, archive, or research-source links. One-fifth of its formerly top-only unused vertical space is redistributed beneath the timeline on fine-pointer canvases." ], "historical_authored_scroll_sequence": [ "the r321 Section 02 opening builds the exact lines After decades of missing pieces and bottlenecks, the last dominoes fell in 2022.; and Advanced voice has tremendous and important capabilities... but also unintended consequences. over a deterministic 1586-by-520 vertical crop of James's exact corrected 1586-by-672 source; the crop removes only top and bottom negative space, does not resample or change any domino, preserves narrow breathing room around the subject, and excludes the decorative corner star; the established 222-millisecond hold and 260-millisecond fade cadence is retained; at r287 the visual remainder is a size container whose displayed frame remains exactly 1586 to 520 while fitting the smaller of the available width and height, with image pixels clipped at that frame and both original half-pixel rules registered to its top and bottom edges; r341 preserves that registration while rendering both structural rules at 1 pixel; transparent single-line all-caps labels retain the slightly smaller regular-weight r285 type, sit in the center of their corresponding domino rows at every viewport width, and read SCIENTIFIC RESEARCH, HARDWARE ACCELERATION, and ACCURATE TRANSCRIPTION AND FEATURE-CODING, with no period after the third title; the transparent two-line ADVANCED VOICE / TECHNOLOGY label uses the same type and remains constrained beneath the waveform domino; the opening contains no explanatory deck, gate, or side annotation", "the second Section 02 state is HARD TAKE-OFF and has no standalone page title; its three timed hero lines state Accurate transcription and coded paralinguistic tagging were the last barriers.; OpenAI and Google Research gave us excellent, open-source solutions to both.; and There was an immediate wave of adoption, new science, and a flood of capital.; beneath them, a larger left-led monospaced list presents six unheaded application cases before equal-width corrected, source-linked Google Research and OpenAI milestone halves; the list is one vertical column on full desktop, two columns at tablet widths, three at short desktop heights, and one on phones; one blank-line equivalent precedes the strip rule and another separates each logo-and-label row from its uppercase date; the complete split-source field is vertically centered between that rule and the authored viewport bottom; Google's label reads TRILLsson VOICE MODEL FAMILY, COMPUTATIONAL PARALINGUISTICS, and EXTRACTION & FEATURE CODING, while its linked publication evidence identifies compact paralinguistic representations, the 2.2 GB CAP12 teacher, the 22 MB smallest distilled model, the 600M-parameter Conformer, and Google's 900M-plus-hour YT-U dataset; OpenAI's label reads WHISPER VOICE MODEL FAMILY, ACCURATE TRANSCRIPTION, and COMMERCIALLY VIABLE ACCURACY, while its linked model-card evidence identifies separately trained scales from Tiny at 39M parameters and 76 MB to original Large at 1.55B parameters and 3.1 GB, plus robust transcription, language-identification, translation, and 680,000 hours of multilingual, multitask supervised audio; it does not describe Tiny as a distillation of Large and makes no voice-production claim; James's supplied 94-by-94 Google Research and 114-by-122 OpenAI Whisper transparent logos are loaded from webv2-assets/section-02/convergence-logos; source links have no red underline and evidence markers are literal neutral-ink hyphen glyphs rather than red bullets; the former red dashed rule, application heading, closing They also began sentence, and standalone headline are absent; the official source URLs include https://research.google/blog/trillsson-small-universal-speech-representations-for-paralinguistic-tasks/, https://research.google/pubs/trillsson-distilling-universal-paralinguistic-speech-representations/, https://openai.com/index/whisper/, and https://github.com/openai/whisper/blob/main/model-card.md; r296 carries the application rule to both viewport edges and the center rule to the footer boundary; r297 links flood of capital to a native independently scrolling detail page that reuses Section 03's public funding and acquisition record, blocks background Section 02 gestures while open, and returns focus on close", "the third Section 02 state is FULLY DEMOCRATIZED ACCESS and builds Advanced Voice System 1995, Advanced Voice System 2010, and Advanced Voice System 2022 left to right while its revised hero lines accumulate downward with 222-millisecond holds and 260-millisecond fades; the exact hero copy is Time and accuracy remained barriers while science and cost had a long run of rapid progress.; When machine-learning AI solved the last challenges, access to voice was fully democratized.; and Today: a decent laptop + scientific literacy + AI competence = cutting-edge voice application.; the milestone captions are Open Release of Praat Voice Software; openSMILE 1.0 and 1st INTERSPEECH Paralinguistic Challenge; and TRILLsson and Whisper Open Releases; the enlarged workload heading reads THE SIZE OF A ONE-HOUR AUDIO FILE AND ITS SPECTROGRAM IS ~5.2 GB OF DATA; a larger four-line ledger above each image separates the architecture-matched 5.2 GB installed-memory equivalent, estimated total system cost, required expertise, and extraction and coding time in hours; the expertise values are Multi-disciplinary scientific team, Advanced Linguistics & Computer Science, and Not required; the installed-memory equivalents are approximately $1.21 million, $1,090, and $150 in constant June 2026 U.S. dollars; the reconstructed capacity-safe total-system estimates are approximately $2.34 million, $6,550, and $2,740 in constant June 2026 U.S. dollars; the selected systems provide 8 GB, 16 GB, and 32 GB respectively; because the source supplies no precise per-file feature-coding duration, James specified a 48-hour working estimate, producing totals of 74 hours in 1995, 48.13 hours in 2010, and 0.13 hours in 2022", "the fourth and final Section 02 state is SCIENTIFIC LITERATURE TIMELINE and builds three science hero lines with 222-millisecond holds and 260-millisecond fades above a horizontally scrollable 2026 through 1981 reverse-chronological research record that opens on the newest work at the left; the exact lines are Linguistics and computer science merged in the 1990s.; Computational paralinguistics had been decades in the making.; and Research accelerated after the 2022 capability convergence.; the superseded historical heading referred to the last 25 years, while the current r342 heading accurately states that the record spans 1981 through 2026; all 89 external source links use equal-weight solid monochrome markers, leaders, and compact topic labels; either mouse button can grab and pan empty timeline space with direct pointer tracking, while Shift-wheel, keyboard navigation, and explicit left and right controls provide movement", "all four historical Section 02 pages shared Section 01's vertical interaction grammar: 120 directional pixels per authored action, a 40-pixel contribution cap per wheel event, a 180-millisecond fresh-gesture reset, one complete automatic sequence per gesture, carried-momentum shielding, immediate upward interruption and exact partial-frame reverse, and a rail that freezes, scrubs, remains frozen after release, and resumes immediately in the next scroll direction; the historical submenu labels were A VOICE TECHNOLOGY CONVERGENCE, B HARD TAKE-OFF, C FULLY DEMOCRATIZED ACCESS, and D SCIENTIFIC LITERATURE TIMELINE with no terminal periods; the completed D-to-03 entry check derived D's final state index from the then-current authored Section 02 beat count" ], "historical_boundary": "Section 02 treats the three Advanced Voice System images as an accessible compression of the underlying science-compute history, not a literal inventory of every system. The source document says basic manual processing could take days but does not provide a precise per-file feature-coding duration; James specified a 48-hour working estimate in the absence of a more precise number. Total workflow time adds that estimate to modeled machine extraction wherever manual feature coding remained necessary. The approximately 1.5 analyst-hours in the source describes speaker segmentation only and must never be presented as feature-coding time. The historical memory and total-system costs are reconstructed explanatory estimates, not live benchmarks, universal minimums, transaction prices, or purchase recommendations. Each reference system has a 64-bit path, storage above 5.2 GB, and installed memory beyond the data set: 8 GB in the 1995 AlphaServer proxy, 16 GB in the 2010 workstation, and 32 GB in the 2022 accelerated laptop. All displayed costs are constant June 2026 U.S. dollars, converted from period nominal list prices using annual-average CPI-U values for 1995, 2010, and 2022 and the latest available unadjusted CPI-U U.S. city average all-items index of 333.952 for June 2026, as published by the U.S. Bureau of Labor Statistics. Stanford DAM is a linked historical commodity-DRAM reference but is not used as a substitute for architecture-matched installed memory. Prerequisites may accumulate without making voice capability gradually solved; the three-line opening, three prerequisite chain labels, and final software outcome carry that argument without an additional gate component.", "paper_manifest": "data/section-02-science-timeline.tsv", "paper_link_boundary": "Each of the 89 records opens an external publisher, archive, or research-source URL in a new browser context. DeCue does not host the papers. Publisher anti-bot or access blocks are recorded as unverified reachability rather than treated as proof of a dead link. Dana can curate the record primarily by removing TSV rows." }, "sentiment_analysis_veil": { "title": "Unmasking Sentiment Analysis", "revision": "r234", "lock_status": "Content remains locked at r234 subject to the r342 native-stack presentation exception and James's r343 static-word-cloud direction: three complete reader-controlled pages replace the historical four-movement, five-state timeline, the company/funding movement appears only in Section 02, and the prepared-remarks cloud is one immutable embedded image whose complete pixels may be resized proportionally but never internally rearranged. Do not otherwise revise without James explicitly reopening Section 03.", "opening_statement": "Voice technology was incorporated into “Sentiment Analysis.”", "sequence": [ "Page one explains that voice technology was incorporated into sentiment analysis long after text-based evaluation and that the invasive expansion escaped notice or scrutiny over the supplied CEO image.", "Page two replaces that image with the restored conceptual text-NLP collage: one immutable 1614-by-546 raster of the approved original 123-term prepared-remarks cloud, an adjective-frequency table, and a 32-period media-mention sentiment illustration. CSS may proportionally resize only the complete cloud image; its internal word placement, type hierarchy, color, and rotation never reflow. The image has concise alternative text, and the original 123-span source is retained inertly for provenance. It explains why the earlier practice was not alarming.", "Page three presents the completed Section 01 indicator suite and attributed vendor-capability evidence as the unseen attack. The six-company opportunity field has moved to Section 02 and is not duplicated here." ], "historical_authored_scroll_sequence": [ "movement one builds Voice technology was incorporated into Sentiment Analysis; Long after the technique was introduced and evaluated, with after italicized; and This concealed an invasive practice that escaped notice or scrutiny over the supplied CEO image", "movement two replaces the CEO image with original conceptual cards for media mentions, adjective use, and sentence length while building Sentiment analysis was initially text-based NLP; Media mentions, adjective use, and sentence length were scored; and None of this was alarming or required a reaction by issuers", "movement three spans two authored scroll states: five editorial company marks remain visible while An entirely new voice capability arrived all at once in late 2022; Then a wave of investment accelerated what was possible; and Unlocking voice created enormous incentives and opportunity all build; all at once and enormous are italicized; the next scroll replaces the marks with five publicly announced capital and transaction records that populate in a quick stagger, Deepgram's Series C row alone carries an orange border, and the sequence ends with the ElevenLabs point Rumored IPO at 11 billion dollars", "movement four begins on the following scroll, replacing the capital record with the completed Section 01 indicator suite and building Invisible proprietary systems, operated silently; Sentiment vendors selling access to your subconscious; and It sounds like science fiction, but it is real and already deployed at scale; its A control is shifted down and left while A, B and C open the original detail dialogs and return to the same attack frame on close; two opaque source cards with 1-pixel top rules attribute marketed capability language to Speech Craft Analytics and Markets EQ" ], "interaction": "Three complete native pages use ordinary reader-controlled vertical scrolling. The company opportunity and funding state is relocated to Section 02. The completed Section 01 indicator suite retains operable A, B, and C detail controls, and closing any detail view returns focus to the same attack frame.", "funding_source_manifest": "webv2-assets/section-3/FUNDING_SOURCES.md", "funding_source_links": [ { "company": "Deepgram", "record": "$12M Series A", "source": "https://deepgram.com/learn/deepgram-series-a" }, { "company": "Deepgram", "record": "$72M Series B", "source": "https://deepgram.com/learn/deepgram-72-million-series-b-defines-future-of-AI-speech-understanding" }, { "company": "Deepgram", "record": "$130M Series C", "source": "https://deepgram.com/learn/press-release-deepgram-raises-series-c" }, { "company": "ElevenLabs", "record": "$19M Series A", "source": "https://elevenlabs.io/blog/elevenlabs-launches-new-generative-voice-ai-products-and-announces-19m-series-a-round-led-by-nat-friedman-daniel-gross-and-andreessen-horowitz" }, { "company": "ElevenLabs", "record": "$80M Series B", "source": "https://elevenlabs.io/blog/series-b" }, { "company": "ElevenLabs", "record": "$180M Series C", "source": "https://elevenlabs.io/blog/series-c" }, { "company": "ElevenLabs", "record": "$500M Series D at an $11B valuation and stated IPO intent", "source": "https://elevenlabs.io/blog/series-d" }, { "company": "Hume AI", "record": "$12.7M Series A", "source": "https://www.hume.ai/blog/hume-ai-raises-usd12-7m-in-series-a-funding" }, { "company": "Hume AI", "record": "$50M Series B", "source": "https://www.hume.ai/blog/series-b-evi-announcement" }, { "company": "Hume AI", "record": "DeepMind team hire and licensing arrangement", "source": "https://techcrunch.com/2026/01/22/google-reportedly-snags-up-team-behind-ai-voice-startup-hume-ai/" }, { "company": "Markets EQ", "record": "Reported total funding of $4.5M", "source_status": "No primary financing announcement naming a Series was located; the visible record intentionally remains unlinked." }, { "company": "Markets EQ", "record": "Purchase of Helios Life Enterprises", "source": "https://www.globenewswire.com/news-release/2024/05/20/2884953/0/en/markets-eq-unveils-strategic-purchase-of-voice-ai-trailblazer-helios-life-enterprises.html" }, { "company": "Markets EQ", "record": "Acquisition by Humach", "source": "https://humach.com/news/humach-acquires-marketseq/" }, { "company": "Nuance / Dragon", "record": "Approximately $16B equity value", "source": "https://news.microsoft.com/source/2021/04/12/microsoft-accelerates-industry-cloud-strategy-for-healthcare-with-the-acquisition-of-nuance/" } ], "vendor_evidence": [ { "vendor": "Speech Craft Analytics", "source": "https://speechcraftanalytics.com/", "distribution_label": "Direct Distribution", "quoted_language": "These micro-patterns reveal the psychological state behind the polished language.", "capability_summary": "The vendor describes measures including stress, confidence, hesitation, pacing, and cognitive load." }, { "vendor": "Markets EQ", "distribution_label": "Available via Bloomberg and FactSet.", "source": "https://www.globenewswire.com/news-release/2024/07/09/2910464/0/en/Markets-EQ-Announces-Availability-of-Platform-Offerings-on-Google-Cloud-Marketplace.html", "quoted_language": "Acting as an AI lie detector for the financial sector.", "capability_summary": "The vendor marketed voice analysis for hidden signals and sentiments. The phrase documents positioning and is not DeCue validation of deception detection." } ], "argument": "Text-based sentiment analysis preceded the post-2022 expansion of voice capability. The publicly announced capital record establishes commercialization without implying misconduct by every pictured company. Producing expressive synthetic voice and extracting meaning from voice draw on overlapping technical understanding, creating a capability that can also target executive speech without notice.", "illustration_boundary": "The text-analysis cards are conceptual explanatory graphics. Company marks are editorial identifiers and do not imply affiliation, endorsement, misconduct, or that every pictured company analyzes executives. The capital wall summarizes publicly announced records but does not itself establish product capability or use against executives. The Section 01 indicator-suite reprise is non-interactive and conceptual; it is not an analysis of the pictured speaker or a real call. Vendor language is narrowly quoted, attributed, and linked as evidence of marketed capability, not accepted as a validated deception-detection claim." }, "what_we_built": { "title": "What We Built", "revision": "r279", "interaction_revision": "r283", "status": "Active three-page native build; not yet locked.", "sequence": [ "Page one combines the counsel-reviewed Silent Suffering origin story, the enlarged linked Journal of Accounting Research cover, the roomier deterministic Brand v2.0 processing-architecture vector, and the three defense-and-preservation statements formerly shown on a separate mixing-board page. The former eavesdropping drawing is absent.", "Page two shows the canonical cyan carrier and orange inner payload being disrupted at the filter while the three sub-perceptual-processing statements remain complete and readable.", "Page three places the exact Safe Harbor recommendation and disclosure with the three secure AWS deployment, immediate processing, and two-hour secure-return statements. The former voice-vault image and standalone Safe Harbor page are absent." ], "historical_authored_scroll_sequence": [ "page one shows the white mixing board while DeCue is, for now, the only available defense for earnings calls; It eliminates the machine-only layer of voice information; and The speaker's natural tone and delivery are preserved for the human ear build in sequence", "a separate scroll replaces the mixing board with the Journal of Accounting Research, a deterministic Brand v2.0 DeCue processing-architecture vector, and the supplied line drawing of a person listening through a glass against a door while We were shocked that \"Silent Suffering\" identified non-consenting CEOs with depression; Our concern grew as we understood the ease of building or acquiring this voice capability; and As synthetic voice is unacceptable for earnings calls, we developed a voice-preserving defense build in sequence", "a third scroll replaces the origin frame with a continuous cyan voice waveform containing an orange inner payload that visibly disrupts and scatters at the filter while We corrupt the unintentional signal channel in sub-perceptual voice; Every function is firmly grounded in well-established peer-reviewed science; and DeCue is computational paralinguistics applied below the human perception threshold build in sequence", "a final scroll replaces the filter frame with the complete, proportionally contained and centered steel voice-vault image whose circular lock contains a voice wave while \"We are deployed in a secure AWS environment for rapid, easy adoption by any issuer.\", \"We accept any format of pre-recorded call and begin to process it immediately.\", and \"We notify you upon completion and return a DeCue'd file via secure link within two hours.\" build in sequence" ], "silent_suffering_link": "The Journal of Accounting Research cover opens https://doi.org/10.1111/1475-679X.12590 in a new tab. The asterisk note is positioned at the bottom of the visual frame, reads For details of the silent suffering paper, click here. and jumps to the exact Silent Suffering entry inside Section 02's research timeline.", "copy_authority": "The visible Silent Suffering sentence is James's counsel-reviewed description of what the authors did. It must not be softened or rewritten without his explicit instruction.", "interaction": "Three complete native pages use ordinary reader-controlled vertical scrolling. The origin page combines the former first two authored states, followed by the filter page and the deployment-and-Safe-Harbor page. No standalone Safe Harbor page follows.", "assets": [ "webv2-assets/section-4/white-mixing-board.jpg", "webv2-assets/section-4/journal-of-accounting-research.jpg", "webv2-assets/reference/decue-pipeline-architecture-r350.svg", "webv2-assets/waveform/vector/light/blue.svg", "webv2-assets/waveform/vector/light/orange-truncated.svg", "webv2-assets/section-4/filter/gate-wide-clean.png", "webv2-assets/section-4/filter/orange-scatter-inside-gate.png", "webv2-assets/section-4/filter/orange-scatter.png" ], "claim_boundary": "DeCue targets machine-only, sub-perceptual information while preserving the speaker's natural tone and delivery for the human ear. Do not restate this as mathematical signal identity, universal efficacy, or perfect preservation under every recording and playback condition without supporting evidence." }, "claim_boundaries": [ "This is not mind reading.", "The autonomic payload is acoustic and paralinguistic information, not literal thought.", "Sub-perceptual describes machine-readable signal below conscious perception; it does not by itself validate a downstream health, affect, intent, or deception inference.", "The hero visualization does not display measured stress scores or results from an actual speaker.", "The health-condition labels indicate areas of voice-marker research; the constructed recurring motif does not diagnose or identify a condition.", "Deception-related acoustic cues are contextual indicators associated with constructs such as arousal, cognitive load, affect, attempted control, or anxiety. The revised C copy describes a simultaneous cluster of directionally consistent cues as a legitimate risk signal when each contributes evidence and the combined pattern is unlikely under a defined null model.", "Even strong individual cues gain evidentiary weight in clusters, but high-stakes uncertainty and deception can appear very similar under acoustic analysis. A cluster may justify attention, investigation, or a calibrated risk score; it does not indicate any probability that a speaker engaged in deception.", "The investor-intent block describes the analysis an investor hopes to obtain; it does not present confidence, affective-state, or deception inferences as validated conclusions about a speaker.", "Performance claims require supporting evidence and measurement context.", "Human-perceived preservation should not be restated as mathematical signal identity.", "The Section 3 capital wall is limited to publicly announced financing and transaction records and does not itself establish misconduct, product capability, or use against executives.", "Section 3 does not depict actual analysis of the pictured speaker, an issuer, or a real call.", "The Section 3 signal-suite reprise is non-interactive and conceptual; its stress values and feature readout are explanatory, not measured results.", "Speech Craft Analytics and Markets EQ language is attributed vendor positioning. Markets EQ's AI lie detector phrase is not a DeCue claim that voice detects deception." ], "page_behavior": { "navigation": "Continuous vertical scroll with a fixed seven-part header rail whose labels retain readable full-screen and tablet sizing. Each rail item navigates directly to its major section. Hover-capable mouse devices open available dropdowns on hover; native click, keyboard, and touch behavior remains available. Section 01 also provides optional in-place A, B, and C detail dialogs. Contact Us, About Us, and Terms of Use persist in the site footer. Contact Us opens email to info@decuetech.com, About Us moves to Who We Are, and Terms of Use opens the complete April 1, 2026 legal text in a native independently scrolling dialog without moving the underlying story.", "persistent_section_labels": [ "Protecting Executive Voice", "Voice Technology Convergence", "Unmasking Sentiment Analysis", "What We Built", "Who We Are", "Frequently Asked Questions", "Log In / Create Account" ], "reverse_scroll": "Ordinary native vertical scrolling is reversible through normal browser movement. The Section 01 comparison itself is directly reversible with the pointer handle or keyboard range control. Dialogs and overlays do not move or reset the page.", "opening_interaction": "Section 01 uses two complete reader-controlled native pages. Page one combines the human-heard copy, full-size manual signal comparison, and AI-operator copy. Page two returns to the clean blue carrier beneath the disclosure boundary. No wheel-triggered timeline assembles the content.", "opening_gesture_control": "The comparison handle accepts pointer drag input and the associated range control accepts keyboard input. Both update the same left-to-right reveal value and preserve registered waveform geometry. Ordinary document scrolling moves between complete pages; an open dialog blocks background progression.", "hero_scroll_states": 2, "history_scroll_states": 4, "veil_scroll_states": 3, "section04_scroll_states": 3, "section04_progress_states": 3, "scroll_runway": "Section 01 has two semantic native pages and no artificial authored-scroll runway.", "history_scroll_runway": "Section 02 has four complete native pages: the domino argument; the 1995, 2010, and 2022 democratization evidence; the six-company incentives-and-opportunity field; and the 89-record 1981-2026 Scientific Literature Timeline. Ordinary scrolling moves between complete pages.", "veil_scroll_runway": "Section 03 has three complete native pages: voice incorporated into sentiment analysis over the CEO image; the earlier text-NLP method; and the unseen-attack indicator suite with attributed vendor evidence. The company and funding state is shown only in Section 02.", "section04_scroll_runway": "Section 04 has three complete native pages: a combined origin-and-defense page; the sub-perceptual filter page; and the secure AWS deployment page containing the exact Safe Harbor recommendation and disclosure. There is no standalone Safe Harbor page.", "section04_r350_vector_contract": "The r350 vector preserves the approved topology, process descriptions, and Brand v2.0 color logic in a roomier 1600-by-640 redraw. Process modules, connector gaps, arrowheads, structural rules, and 32-to-36-unit text roles are enlarged. At r352 the process descriptions use regular weight and the redundant uppercase stage over-labels are absent. At r353 the Scientific Foundation and Tools & Libraries headings are centered within their supporting boxes. The complete semantic contents are repeated in the HTML caption.", "section05_layout": "Section 05 is a single Who We Are page. James Palczynski, Prof. Dana Carney, and Seth O'Neal appear together in equal desktop columns; each is identified as a Co-Founder alongside the applicable Chief Executive Officer, Chief Scientific Officer, or Chief Technology Officer operating title. Each compact card retains the portrait, name, operating title, direct email contact, and a View Biography control. Those controls open one shared native dialog with separate complete founder profiles, independent scrolling, boundary wheel and touch containment, Escape and backdrop close, and exact focus return. James's biography is user-supplied; Dana's official biography, authored by Dana and published by Berkeley Haas, is reproduced with its source linked in the detail view; Seth retains the current DeCue biography. James and Dana use the user-supplied originals from Headshots, proportionally resized and contained without face cropping. Seth uses the original public portrait without the rejected grainy r260 restoration or the former card filter; the biography frame crops only the small lower-right generative-image sparkle baked into that source. Below the cards, the Contact Us block exposes info@decuetech.com and an accessible service-updates dialog. At r300, the dialog requires an email address and explicit opt-in consent, then posts a distinct service_updates request that is stored and sends an SES notice to info@decuetech.com without opening the visitor's email application. The complete biographies and contact content remain static semantic HTML for assistive technology and agent access.", "section05_transition": "The Safe Harbor box is integrated into the final What We Built page. Who We Are, the FAQ, and Log In / Create Account then participate in the same ordinary native document flow. Direct navigation aligns each destination below the fixed header. No authored boundary dissolve is required.", "dissolve_interaction": "The former wheel-triggered Section 01 dissolve is historical. The current comparison is manually reversible, and the second native page presents the completed clean-carrier disclosure boundary without an authored transition timeline.", "section_one_progress": "Section 01 has no authored stage rail. The keyboard-operable range input exposes the comparison value, and the visible microphone handle tracks that same value.", "theme_policy": "light-only; the former URL-selected dark rendering path was removed at revision r161 and may be reconsidered later", "brand_mark": "The transparent high-resolution DeCue Technologies PNG is anchored in the upper-right of the fixed header. Activating it returns to the top of the current native Section 01 composition.", "reduced_motion": "The same complete native pages remain available; nonessential transitions and animations are disabled." }, "go_forward_project": { "baseline": "Revision r358 is the current local DEV review checkpoint layered on the r340 GitHub review-branch checkpoint. It is not yet committed, pushed, CI-passed, or deployed; dev.decuetech.com remains r340-hero-half-gap until explicit publication. The r358 review uses ordinary reader-controlled native document flow; a literal 11pt floor for live semantic interface text; the approved original prepared-remarks cloud embedded as one immutable proportionally scalable image; full-width hero lines; 1px structural lines outside purposeful four-sided component outlines; canonical blue underlined interactive text with cyan hover and keyboard-focus glow; visible scrollbars; active navigation reveal; a footer-safe 89-record Scientific Literature Timeline spanning 1981 through 2026; corrected active evidence and funding-source links; synchronized visible, accessibility, and agent-readable descriptions; an authored 1920-by-1200 design canvas with viewport-fit runtime plates so one complete page is visible at any resolution, including 2560-by-1080; a deliberate entry slice above the Section 01 closing argument; a four-to-one redistribution of unused space around the Section 02 timeline; and centered Scientific Foundation and Tools & Libraries headings in the Section 04 architecture graphic. Production status remains unchanged.", "r341_authority_exception": "Where an older historical entry describes a half-pixel structural rule, r341 preserves the authored registration but renders that rule at 1 pixel. Only purposeful four-sided component outlines may retain a 0.5-pixel border. This global conformance exception preserves substantive locked copy, imagery, and choreography while applying James's requested spelling, punctuation, and capitalization corrections.", "handoff": "docs/handoffs/DECUE_WEBSITE_R343_LOCAL_REVIEW_HANDOFF_2026-08-12.md", "authority": "Current user direction and the source-verified local r358 artifact outrank the handoff, older machine-readable summaries, older project notes, and the legacy DeCue site. Section 01 remains content-locked at r181 subject to its explicit later exceptions. Section 02 remains layout- and choreography-locked subject to its explicit native-stack exceptions; the domino asset was explicitly updated by James on August 3, 2026. Section 03's prepared-remarks cloud is explicitly locked as the immutable r343 raster and may only be resized as a complete image. Neither section may otherwise be revised without a new explicit instruction from James. Palantir supplies interaction and visual mechanics; it is not a literal page baseline.", "chapter_pattern": "The current r353 review preserves vertical storytelling as ordinary native document flow. Sections 01 through 04 contain complete reader-controlled pages rather than wheel-assembled timelines: 2, 4, 3, and 3 plates respectively. Dense evidence remains available through clearly titled optional disclosures, dialogs, and source links.", "remaining_sections": [ { "rail": "02", "title": "VOICE TECHNOLOGY CONVERGENCE", "status": "Layout- and choreography-locked subject to the current explicit native-stack exceptions. Four complete reader-controlled pages present A the seven-line domino argument with no detached capability box, B democratization through the Advanced Voice Systems plus compact Google TRILLsson and OpenAI Whisper evidence, C the six-company incentives-and-opportunity field moved from Section 03, and D the 89-record Scientific Literature Timeline spanning 1981 through 2026. The submenu labels are exactly VOICE TECHNOLOGY CONVERGENCE, DEMOCRATIZATION OF VOICE, INCENTIVES AND OPPORTUNITY, and SCIENTIFIC LITERATURE TIMELINE. James's corrected 1586-by-672 domino image and deterministic 1586-by-520 crop remain authoritative and unchanged. Ordinary scrolling moves between complete pages; the older HARD TAKE-OFF/FULLY DEMOCRATIZED ACCESS timed-page account is historical provenance, not current behavior." }, { "rail": "03", "title": "UNMASKING SENTIMENT ANALYSIS", "status": "Content remains locked at r234 subject to the r342 native-stack exception and James's r343 static-word-cloud direction. The current reader-controlled sequence contains three complete pages: the CEO-image introduction, the original text-NLP collage with its prepared-remarks cloud frozen as one immutable embedded image, and the unseen-attack indicator suite with attributed Speech Craft Analytics and Markets EQ evidence. The company and funding movement is shown only in Section 02. Ordinary scrolling replaces the historical four-movement, five-state authored timeline." }, { "rail": "04", "title": "WHAT WE BUILT", "status": "Active r353 native-stack adaptation of the r279 content. Three complete reader-controlled pages present: the combined Silent Suffering origin/evidence frame with enlarged journal and roomier architecture redraw; the canonical cyan-and-orange filter disruption; and secure AWS deployment and file return beside the exact Safe Harbor box. The architecture descriptions use regular weight with redundant uppercase stage over-labels removed, and both supporting-box headings are centered. The door-listening illustration, voice vault, and standalone Safe Harbor page are absent. Section 04 is not yet locked." }, { "rail": "05", "title": "WHO WE ARE", "status": "Active one-page build at visual revision r284 with the service-updates workflow updated at r300 and current r342 native document flow. James Palczynski, Prof. Dana Carney, and Seth O'Neal appear together in equal compact columns as Co-Founders alongside their operating titles, portraits, direct email contacts, and View Biography controls. Seth's original public portrait is used without the rejected synthetic restoration or former card filter, and its baked-in lower-right sparkle is excluded from the biography frame. One shared accessible dialog presents all three complete profiles without changing the underlying page position. A Contact Us block below the cards exposes info@decuetech.com and a separate consent-based service-updates dialog whose stored request sends an SES notice directly to that address. Direct navigation lands at the intended top composition; the former 05/06 boundary dissolve is historical." }, { "rail": "06", "title": "FREQUENTLY ASKED QUESTIONS", "status": "Current review content prepared locally at r305 from DeCue_FAQ_Current_Review.docx and presented in r342 ordinary native document flow. The 29 sequential entries appear in 10 semantic categories; all three FAQ TODO items are included and the evidence-sensitive health answer uses verified wording. The Safe Harbor answer includes the exact disclosure from #why-it-matters. The former FAQ-to-account boundary dissolve is historical." }, { "rail": "07", "title": "LOG IN / CREATE ACCOUNT", "status": "The public site does not collect credentials or process customer audio. Log In and Create Account hand off to the secure DeCue customer portal, and the full-width Contact Us box directly beneath them opens email to info@decuetech.com. Canonical portal routes are /login, /signup, and the authenticated /portal application. Section 07 participates in ordinary r342 document flow; the former 06/07 reversible dissolve is historical. On dev.decuetech.com, account actions are mapped directly to the isolated development portal at dev.portal.decuetech.com. Route-level checks for /login, /signup, and /portal passed on 2026-08-05; authenticated MFA, upload, processing, billing, and administration still require separate acceptance with real environment access. Production uses portal.decuetech.com." } ], "faq": { "status": "Prepared locally at r305 from the current 29-question FAQ review document; not approved for production publication.", "placement": "06 / Frequently Asked Questions", "source": "prototypes/website-v2/SECTION_06_FAQ_WORKING_REFERENCE.md; original DOCX provenance is retained there but the DOCX is not present in this checkout", "content": "29 sequential Q&A entries across 10 categories, with the investor-objection and anti-AI questions first.", "numbering": "The current review source contains 29 sequential entries. The public page preserves that order and presents them as 01 through 29.", "safe_harbor": "The placeholder in the final answer is replaced with the exact recommended disclosure from the canonical #why-it-matters page.", "implementation": "Every answer is static canonical HTML inside a native details disclosure. The complete content is also mirrored in faq_content and llms.txt." }, "synchronization_rule": "Substantive changes to narrative, claims, section titles, interaction contracts, or source boundaries must be synchronized across semantic HTML or transcript, README.md, agent-context.json, llms.txt, the relevant provenance record, and shared-memory MCP when the decision is durable." } }