Language Code isteğe bağlı
Language of the audio as an ISO-639-1 (e.g. 'en') or ISO-639-3 (e.g. 'eng') code. Set to 'auto' to detect the language automatically. Setting a specific language can improve accuracy for noisy or unusual audio.
Diarize isteğe bağlı
Identify and label different speakers in the audio. When enabled, each word in the output includes a 'speaker_id'. Supports up to 32 speakers.
Kapalı Diarize Num Speakers isteğe bağlı
Maximum number of speakers expected in the audio. Helps the model with diarization. Set to 0 to let the model decide. Only used when 'diarize' is true.
Timestamps granularity isteğe bağlı
Granularity of word timestamps in the output. 'word' returns start/end times for each word, 'character' adds per-character timing, 'none' omits timestamps.
None Word Character
Tag Audio Events isteğe bağlı
Tag non-speech sounds in the transcription, like (laughter), (footsteps), or (applause).
Açık Tag Audio Events No Verbatim isteğe bağlı
Remove filler words ('um', 'uh'), false starts, and disfluencies from the transcript. Produces a cleaner, more readable output.
Kapalı No Verbatim Keyterms isteğe bağlı
Comma-separated list of words or phrases to bias transcription towards. Useful for product names, technical terms, or proper nouns. Up to 1000 terms, max 50 characters each.
Temperature isteğe bağlı
Sampling temperature. Higher values produce more diverse, less deterministic output. Set to -1 to use the model default (usually 0).
-1 0 1 2
Seed isteğe bağlı
Random seed for reproducible outputs. Set to -1 to use a non-deterministic seed.
