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Yeah, I suspect the problem here is that computer transcription makes mistakes and then a summarizing LLM treats whatever it outputs as gospel. Automated trans
by smelendez 1mo ago
Yeah, I suspect the problem here is that computer transcription makes mistakes and then a summarizing LLM treats whatever it outputs as gospel.
Automated transcription for anything official is scary to begin with, because some noise in the background is all it takes to turn "I've never taken mushrooms" to "I take mushrooms," or whatever. And then the LLM will simply report "Patient reported using mushrooms."
- rhdunn 1mo agoSpeech recognition is a notoriously difficult problem to solve. It can work great as a first pass that someone can fix up, but not on its own. This is why having sentence/clause and word-level transcription markers along side a recording help. One of the main issues is around homophones in an accent (Adam/Atom in American English, Bath/Barf in London English, etc.). Not to mention pronunciation variations due to fast speech, speech impedements, or parts of words side-by-side that sound like a different word. Another big issue is around misaligned training data. For example, Whisper is known to hallucinate on silence [1]. [1] Investigation of Whisper ASR Hallucinations Induced by Non-Speech Audio (https://arxiv.org/html/2501.11378v1 https://arxiv.org/html/2501.11378v1)