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 version has 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 version has implementation to predict word timestamps and provide a more accurate estimation of speech segments when transcribing with Whisper models.
condition_on_previous_text
booleanprovide the previous output of the model as a prompt for the next window
Default value: true
temperature_increment_on_fallback
numbertemperature to increase when falling back when the decoding fails to meet either of the thresholds below
Default value: 0.2
webhook
fileThe webhook to call when inference is done, by default you will get the output in the response of your inference request