The Human Reference & Safety Layer for Voice AI Alignment 

_________________________________

Misalignment is Costing You User Trust & Millions in Abandonment

_________________________________

 

      Voice AI is at an inflection point right now where acoustic realism, latency and emotion labels are commodities that are no longer enough - leaving most companies optimizing & solving the wrong variables.  Perceptual alignment, tonal intent and preventing tonal hallucinations now matter more in determining if agents are actually trusted in real human-AI interactions.

 

    Users Abandon Technically Perfect Voice AI Because of Prosodic Inappropriateness: Tone Doesn't Match Context

 

     Further, if your model cannot interpret tonal ambivalence, stabilize prosody at inference-time, and mitigate tonal sycophancy, users perceive it as 'false confidence' - leading to abandonment in high-stakes contexts (healthcare, finance, autonomous systems) - deepening the Uncanny Valley, not crossing it. 

 

     Whether you’re evaluating how your agents sound or negotiating how human voices are licensed, protected, or integrated into AI, the inflection point is the same: tonality is no longer style - it’s an alignment and IP surface for native audio AI. The companies who pivot to prosodic alignment will dominate. The ones who don't will keep debugging 'UX issues' that are actually tonal mismatches

           •costing conversions

           •costing trust and

           •costing revenue

 

(For Tier 1 Labs & Frontier Teams Shipping Voice at Scale)

______________

Request Embodied Voice Licensings

________________________________________________________________________________________________________

 

 

 

The Uncanny Valley of Authenticity: A Crisis of Trust in Voice AI

 

Modern voice systems can sound fluent, expressive, and technically impressive - yet still trigger discomfort, disengagement, or quiet rejection.

 

  • Teams feel it in demos.

 

  • Users feel it immediately.

 

  • Metrics often miss it entirely.

 

This isn't just a modeling problem; it's a real-time inference challenge and it's a perceptual alignment problem that drives user mistrust, regulatory scrutiny, and real-world risk. This includes the insidious problem of tonal sycophancy, where AI models inadvertently adopt a tone designed to "please" rather than accurately convey information, leading to user manipulation and distrust. The industry has mastered sound, but not listening and stabilizing tonal intent at the moment of interaction.

 

_________________________________

 

 Tonality as the Stabilizing Ground-Truth Data of True Intelligence

 

Ronda Polhill’s "Tonality as Attention" framework and the TonalityPrint dataset represent a pivotal shift. We move beyond surface-level fidelity to focus on prosodic weighting and attentional mechanisms that govern the realities of human communication, providing the ground-truth biometric data for

 

  • inference-time prosodic calibration

 

  • real-time tonal alignment and 

 

  • proactive sycophancy mitigation

 

 

Crucially, we treat tonal ambivalence - the subtle complexities and uncertainties in human speech - as a signal, not an error.

 

This is the key to truly bridging the Uncanny Valley and establishing a stable human anchor in a fast-moving voice model landscape.

 

_________________________________

 

 

Frontier Perceptual Audit: Diagnose Your Model’s Human Attunement

 

Before you invest further, know where you stand. The Frontier Perceptual Audit™ is a rapid, high-value assessment for Tier 1 labs and quick moving teams, designed to objectively measure your voice AI’s current tonal intelligence and its ability to navigate nuanced human interaction. It’s a low-friction diagnostic that provides immediate, specific and actionable insights.

 

  • Sycophancy Detection & Mitigation Analysis Available: Identify instances where your model exhibits tonal sycophancy and receive strategies for its mitigation.

 

_________________________________

 

 

Beyond the Audit: Scale Human Alignment with Embodied Voice Licensing

 

Once you understand your audio AI model’s tonal landscape, the next step is to build a truly human-aligned future. Embodied Voice Licensing provides the foundational IP and specialized datasets to integrate Ronda’s unique tonal intelligence directly into your core systems. This is the strategic investment for sustained competitive advantage, ethical compliance, and unparalleled user trust.

 

_________________________________

 

 Strategic Access to Deep HITL Expertise:

  • Independent Research

  • Unrivaled Expertise

  • Real-World Performance Data (NOT lab results) 

 

Ronda Polhill is the architect of the "Tonality as Attention" framework. She is an independent voice alignment researcher focused on tonal perception, human-AI interaction trust, and interpretive alignment in synthetic voice systems. 

 

Polhill's deep work integrates professional voice experience, perceptual tonality research, and alignment methodology development to support emerging evaluation domains in voice AI. It stands independently of institutional affiliation - by design.

 

This ensures unbiased, pure research focused solely on solving the most challenging problems in voice AI. Her documented research (Tonality as Attention white paper, TonalityPrint  voice dataset) is archived on Zenodo for provenance and partner review.

 

 

 

  • TonalityPrint Voice Dataset & README - Specialized Perceptual Alignment Reference Dataset - (Download Here:  Zenodo Jan 2026)

 

  • Independent Human-Centered Voice Research

 

  • Documented Unsolicited Feedback on Trust, Warmth, and Non-Uncanny Presence

 

 

Beyond Academic Research

 

Ronda's expert-practioner performance & observed patterns of her 'AI-Adjacent, yet Trusted' voice tonality documented over nine months:

 

  • 35.85% average sales conversion across 8,873 B2C voice calls (vs. 18-25% industry baseline)

 

  • 168 unsolicited voice-specific compliments documented from customers

 

  • 68 unsolicited "AI-quality" favorable descriptors from customers

 

 

 

_________________________________

 

 

 

Who This Is For ( and Who it is Not For)

 

 

For Those Building the Voice AI Models 

 

 This ACTIONABLE work is for you if you are responsible for audio AI model

performance, stability, and alignment at a technical level.

 

 

✓ Frontier Labs & SLM Researchers shipping voice directly to humans and needing

to prevent tonal hallucinations and model drift.

 

✓ AI Safety & Alignment Researchers red-teaming for inappropriate tonal manipulation,

ensuring voice AI doesn't sound certain when it is, in fact, uncertain, and specifically

addressing sycophancy mitigation in human-AI interaction.

 

✓ Engineering Leads building real-time conversational agents that require inference-time

tonal stability and robust handling of prosodic edge cases.

 

✓ Teams Optimizing Beyond Legacy Benchmarks who recognize that metrics like acoustic fidelity

and latency are no longer sufficient differentiators for true human-AI interaction.

 

 

 

 

For Those Shipping the Voice AI Products

 

This ACTIONABLE work is for you if you are responsible for user adoption, conversion

rates, and the commercial success of your voice AI products.

 

 

✓ Voice AI Startups experiencing high user abandonment rates that cannot be explained

by traditional UX metrics.

 

✓ Enterprise Platforms where a 1% improvement in voice-driven conversion or retention

translates to millions in revenue.

 

✓ Companies for who voice trust and brand safety are critical product differentiators against

commoditized TTS solutions.

 

✓ Organizations deeply focused on stabilizing long-term user adoption and trust across rapidly changing

models and product iterations.

 

 

 

Not a Good Strategic Fit For Everyone in Voice AI

 

This  ACTIONABLE work is NOT for:

 

✗ Teams optimizing benchmark-only metrics

 

✗ Commodity TTS pipelines where prosodic quality doesn't matter

 

✗ Synthetic diversity at scale

 

✗ Teams unconcerned with felt experience or ethical implications

 

✗ Companies satisfied with 18-25% conversion baselines

 

 

 

 

_________________________________

 

 

If You’re Building Voice AI that Interacts with Humans at Scale, the Only Question is Timing

 

Availability for Frontier Attention Audits and Strategic Licensing Partnerships are intentionally limited. 

 

 

 

Secure your position at the forefront of human-aligned voice AI