openai/whisper-timestamped-medium.en
Whisper is a set of multi-lingual, robust speech recognition models trained by OpenAI that achieve state-of-the-art results in many languages. Whisper models were trained to predict approximate timestamps on speech segments (most of the time with 1-second accuracy), but they cannot originally predict word timestamps. This variant contains implementation to predict word timestamps and provide a more accurate estimation of speech segments when transcribing with Whisper models.
Whisper is a set of multi-lingual, robust speech recognition models trained by OpenAI that achieve state-of-the-art results in many languages. Whisper models were trained to predict approximate timestamps on speech segments (most of the time with 1-second accuracy), but they cannot originally predict word timestamps. This variant contains implementation to predict word timestamps and provide a more accurate estimation of speech segments when transcribing with Whisper models.
Input
Please upload an audio file
task to perform 2
optional text to provide as a prompt for the first window.. (Default: empty)
temperature to use for sampling (Default: 0)
language that the audio is in; uses detected language if None; use two letter language code (ISO 639-1) (e.g. en, de, ja). (Default: empty)
chunk level, either 'segment' or 'word' 2
Chunk Length S
chunk length in seconds to split audio (Default: 30, 1 ≤ chunk_length_s ≤ 30)
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