The Human Reference Point for Voice AI Alignment 

For Voice Systems Interacting with Humans at Scale.

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Single-speaker tonal datasets, perceptual audits, and embodied voice licensing used to eliminate uncanny-valley effects and stabilize trust across rapidly evolving voice AI models.

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• Tonality as Attention - 590+ downloads (Zenodo)
• TonalityPrint Voice Dataset - Jan 2026
• Independent Human-Centered Voice Research
• Limited Availability

 

Request  Confidential Strategic Access

For frontier labs, voice AI CEOs, and teams shipping voice to humans.

 

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Voice Models Are Advancing Faster Than Human Trust Can Be Measured

 

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 gap is not a modeling problem.
It is a perceptual alignment problem.

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Capability Scales. Trust Does Not.

 

Base models improve rapidly.
Fine-tuning improves accuracy.
But felt experience - warmth, safety, presence, credibility, reciprocity - does not converge automatically.

 

As models change faster, teams lose a stable human reference point.

 

That instability is where uncanny valley emerges.

 

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A Stable Human Anchor in a Fast-Moving Model Landscape

 

I develop and license single-speaker tonal reference systems designed for tonal control, continuity, and perceptual interpretability.

 

Unlike large, diverse datasets optimized for scale, this work prioritizes:

 

• Tonal coherence across contexts
• Embodied trust signals users respond to intuitively
• Perceptual diagnostics teams can act on
• Continuity across model upgrades

 

This approach is intentionally scarce.

It cannot be scraped, crowdsourced, or synthesized away.

 

 

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Strategic Access to Deep HITL Expertise

 

Available on a limited basis:

 

Tonal Reference Dataset Licensing
Single-speaker, high-control dataset for perceptual calibration and research.

 

Perceptual Voice Audits
Short-cycle evaluations identifying where systems drift into uncanny or misaligned territory.

 

Embodied Voice Licensing
Use of a pre-trusted human voice as a gold-standard reference for demos, alignment, or product validation.

 

Executive & Research Briefings
Private, high-signal sessions for leadership teams navigating voice AI uncertainty and ambivalence.

 

 

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Who This Is - and Is Not - For

 

This work is for teams who:

 

• Ship voice directly to humans
• Care about trust, safety, and long-term adoption
• Notice when “something feels off” before users complain
• Need stability across rapidly changing models

 

This work is not for:

• Benchmark-only optimization
• Commodity TTS pipelines
• Synthetic diversity at scale
• Teams unconcerned with felt experience

 

 

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Independent, Documented

 

Research underpins:

 

• Tonality as Attention (Zenodo)
• TonalityPrint Dataset & README
• Documented unsolicited feedback on trust, warmth, and non-uncanny presence

 

The dataset architecture and technical documentation are archived on Zenodo for research and partner review, and provenance. The work stands independently of institutional affiliation - by design.

 

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If You’re Building Voice AI for Humans, the Only Question is Timing

 

Request Confidential Strategic Access

 

Availability is intentionally limited.

 

 

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