Is Detecting Diseases Based on 45 s of Voice Accurate? (Henry O'Connell)

Ambient speech technology is now common for documentation; but what if the biggest opportunity isn’t transcription?

In this episode of Faces of Digital Health, host Tjasa Zajc speaks with Henry O’Connell (CEO of Canary Speech) about voice biomarkers: how conversational speech can support detection and monitoring of neurological and behavioral health conditions—without relying on “what you say,” but on how the nervous system produces speech.

We cover:

Why decades of word-based voice biomarker research struggled to reach clinical practice
Canary’s approach: analyzing the “primary data layer” behind speech production
How ~45 seconds of conversational speech can generate millions of data elements for analysis
Reported accuracy differences between progressive neurological diseases and behavioral health
Why validation must be repeated across languages and populations
Real-world use in primary care screening, clinical trials, and workflow-integrated ambient systems
Ethics and guardrails for wellness and workplace use
Emerging operational use cases, including aggression risk signals in hospital rooms

Notes:

00:12 Intro: voice biomarkers beyond ambient documentation
01:03 Potential vs reality: what voice can (and can’t yet) prove clinically
01:54 Why earlier voice-biomarker work focused on words—and why it stalled
06:34 The “intuition” problem: we hear mood without words
07:33 Canary’s clinical-first approach and global clinical partnerships
08:39 Do you need long-term data? (Agatha Christie example)
09:41 Method: ~45 seconds of conversational speech, ambient capture
10:36 Scale: 2,590 features every 10ms (~13M data elements)
11:02 Where the features come from (vocal cords, respiration, resonance)
14:36 How models are built: IRB, clinician ground truth, ML correlation
17:30 Accuracy + adoption: why it’s not standard practice yet
18:22 Reported performance: 98%+ neuro, ~80s behavioral health
22:44 Culture/language bias concern: why validation per language matters
24:22 Guardrails: validate every new language and population testing
31:07 Why read-speech scripts misled the field; conversational-only stance
34:16 What changed: AI, compute, real-time streaming, workflow fit
37:10 How it’s used: screening vs suspected disease; incidental findings
39:24 Primary care example: postpartum depression flagged despite “I’m fine”
47:56 Wellness/employee use: de-identified dashboards and ethics
53:42 Technical requirements: device capture, signal-to-noise checks
57:10 In-room monitoring: aggression risk signals for staff safety
1:02:22 Clinical trials: pre-screening + measuring therapeutic impact
1:07:14 Global rollout: regions, languages, and partnerships
1:09:42 Consumer access: wellness product planned in 2026
1:12:32 Wrap-up: why this matters as cognitive health needs grow