Whisper Large V3 Turbo
A speech recognition model released by OpenAI as part of the Whisper series. It supports multilingual transcription and is designed for fast operation at low cost.
Timeline (last 90 days)
A certain speech recognition model is only 164MB in size and transcribes one hour of audio in about 20 seconds on an ordinary thin-and-light laptop, with a word error rate of 5.21, outperforming mainstream models such as Whisper Large V3 Turbo; it currently supports only English.
The project uses the OpenAI Whisper Large V3 Turbo model for speech transcription, and in measured tests transcribing one sentence costs less than one-thousandth of a cent.
Whisper Large V3 Turbo improves inference speed by reducing the decoder layers from 32 to 4 while maintaining recognition accuracy close to the original.
The project uses the Whisper Large V3 Turbo model, sending Base64-encoded audio data to the /audio/transcriptions endpoint for transcription.
Parakeet Redux can run on CPU with a disk footprint of 178 MB, compared to the 1.6 GB of Whisper Large V3 Turbo (Whisper CPP version).
All Facts (5)
A certain speech recognition model is only 164MB in size and transcribes one hour of audio in about 20 seconds on an ordinary thin-and-light laptop, with a word error rate of 5.21, outperforming mainstream models such as Whisper Large V3 Turbo; it currently supports only English.
50%UnverifiedThe project uses the OpenAI Whisper Large V3 Turbo model for speech transcription, and in measured tests transcribing one sentence costs less than one-thousandth of a cent.
50%UnverifiedWhisper Large V3 Turbo improves inference speed by reducing the decoder layers from 32 to 4 while maintaining recognition accuracy close to the original.
50%UnverifiedThe project uses the Whisper Large V3 Turbo model, sending Base64-encoded audio data to the /audio/transcriptions endpoint for transcription.
50%UnverifiedParakeet Redux can run on CPU with a disk footprint of 178 MB, compared to the 1.6 GB of Whisper Large V3 Turbo (Whisper CPP version).
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