A verbatim-transcription variant of OpenAI Whisper fine-tuned by Nyra Health for fast, precise ASR with crisp word-level timestamps, filler detection ('um', 'uh'), and reduced hallucinations. First place on the OpenASR Leaderboard for verbatim datasets.
A solid 1.55B-parameter dense audio model from Nyra Health. Treat the modality benchmarks above as the leading indicator of fit — composite scoring across modalities is still maturing.
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CrisperWhisper is an advanced fine-tune of Whisper Large by Nyra Health aimed at true verbatim transcription — every stutter, false start, filler and pause is captured rather than smoothed over as standard Whisper does.
[UM], [UH], stutters, repetitions, and false startsMedical scribing, linguistic/phonetic research, discourse analysis, legal transcription, dubbing/subtitling, and any pipeline that requires exactly what was said.