Henry O’Connell, CEO of Canary Speech

— Voice Biomarkers, and Real-Time Clinical Support

Summary

Canary Speech turns everyday conversation into clinical-grade insight. Henry O’Connell explains how ambient listening analyzes 2,590 vocal biomarkers every 10 milliseconds to produce about 16 million data points per minute. The system returns real-time scores for anxiety, depression, cognitive health, Parkinson’s, multiple sclerosis, and more without interrupting the doctor–patient relationship. We cover continuous monitoring, aggression detection for nurse safety, patents and IP strategy, data security, deployment across devices, and how ambient AI moves healthcare beyond chat.

Key Takeaways

• Voice is a rich biometric after DNA and can signal mental and neurological conditions through vocal biomarkers.
• Ambient listening integrates into clinical workflows without test-taking or friction.
• Canary analyzes 2,590 features every 10 milliseconds for roughly 16 million data elements per minute.
• Real-time clinical decision support returns multi-condition scores to physician devices.
• Device-agnostic capture works via phones, tablets, telehealth, call centers, and wearables.
• New continuous monitoring flags risk in rooms and can measure aggression levels to protect nurses.
• Canary reports 14 issued patents with 12 pending and approximately $26M raised.
• Data security aligns with hospital-grade standards and ISO certifications.
• Primary care becomes a force multiplier with earlier referrals and standardized objective metrics.
• Longitudinal deltas compare a patient’s voice across visits to track change over time.

Who This Episode Is For

• Founders in AI, digital health, and human–computer interaction
• Clinical leaders evaluating ambient AI and decision support
• Product and data teams shipping voice and real-time ML at scale
• Investors tracking voice biomarkers and healthcare AI infrastructure

Frameworks Discussed

Ambient AI Pipeline

1. Permissioned audio capture in natural conversation
2. Speaker separation, sample quality checks, feature extraction
3. ML models for condition-specific scoring in near real time
4. Delivery into clinical workflows and notes platforms

Clinical Decision Support Loop

1. Objective voice-based scores
2. Physician interpretation and next best question
3. Referral decision and follow-up
4. Longitudinal tracking across visits

Longitudinal Delta Method

Compare patient voice features across time to quantify change and trend risk.

Safety and Operations Layer

Aggression detection with green yellow red indicators to reduce nurse assaults and burnout.

Compliance and Trust Stack

Hospital-level security posture, ISO certifications, integration with existing transcription and EHR workflows.

IP and Defensibility

Patents for voice biomarker detection, ambient AI methods, longitudinal comparison, and LLM fusion.

Notable Numbers

• 2,590 vocal biomarkers analyzed every 10 milliseconds
• About 15.5 to 16 million data elements per minute of speech
• Real-time scores returned during normal clinical conversations
• 14 issued patents and 12 pending reported in the conversation
• Approximately $26M raised to date reported in the conversation

Resources

• Canary Speech
• Henry O’Connell on LinkedIn
• [email protected]

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