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Speech Therapy

Built at The Future of Agentic AI in Healthcare - Abridge x Anthropic x Lightspeed · Jul 18, 2026 · San Francisco, CA

Speech Therapy — Demo video

Pre-Check — situational speech profiling for speech-language pathologists The clinic is a non-representative speaking situation: people who stutter often speak very differently with a clinician than on a phone call or ordering food — so SLPs assess a sample that doesn't reflect the disorder. Worse, standard ASR can't even capture the data: it erases, smooths, or garbles stuttered speech (we tested it — sound repetitions come back as the wrong words entirely). Pre-Check runs a pre-visit session: a patient talks with a calm voice agent about their speech (the baseline sample), then takes a simulated phone call — ordering a pizza — that elicits real-situation speech. A voice interface built for this audience: tap-to-finish turns, no VAD cutoffs, it never hangs up on you. Recordings run through a two-engine pipeline: CrisperWhisper for verbatim words + timestamps (blocks detected from inter-word gaps, repetitions from tokens) fused with LLM-Dys for dysfluency type classification, anchored per turn. The SLP gets a one-page profile: how speech changed across situations, playable timestamped evidence for every detected event, and a side-by-side of what standard ASR heard vs. what was actually said.

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