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Every feature below is off unless the table says otherwise, and you turn it on per request. On files send the option as a form field, on live audio as a query parameter, and with the OpenAI SDK in extra_body.

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At a glance

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File transcription

Send a file, get the text. Any common format; long files are cut at quiet points and joined. This is the most accurate way. See Native API or OpenAI-compatible API.

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Live transcription

Send audio over a WebSocket and receive partial text while the person speaks and final text when a sentence ends. Show partial as live text and send final to your language model. The sentence ends after about 0.8 s of silence, or at once when you send flush. See Native API (/v1/stream) or OpenAI-compatible API (/v1/realtime).

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Asynchronous jobs

For long recordings the request does not have to stay open: send webhook_url, get a job id at once, and receive the result on your server. You can also read it with GET. Up to 4 hours of audio. Instead of uploading, file_url lets the server download the file. See Asynchronous transcription.

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Number and text formatting

On by default (normalize=true). The final text is written the way people write it: “bin iki yüz elli lira” becomes “1.250 TL”. normalize=false returns the spoken words. In Turkish three more options work with it: partial text on live audio is not formatted, only final is.

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Hints

Tell the recogniser which names and places to expect (Turkish). hints takes your own phrases, comma or newline separated; phrase :3 gives one phrase its own boost. hint_context adds a built-in list: mugla, izmir, manisa, aydin, denizli. Use it for customer names, street names and product names.

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Language model

mode=normal makes file recognition with model=umay use the language model where the model has one. It takes about 40-60 % more processing time and helps most on clean read speech. The default mode=fast does not use it.

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Gender detection

gender_detection=true gives each speaker’s gender with a confidence percent (50-100). On live audio it arrives about 2 s after speech starts and is updated later; it never delays the text.

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Diarization

diarize=true labels who said what: S1, S2, … in order of appearance (A, B, … with OpenAI model names). max_speakers sets the upper bound (default 8). Use it for conversations in one channel.

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Speaker lock

speaker_lock=true makes only the first speaker’s speech text; other voices come as ignored, so they do not reach your language model. Each segment carries similarity, how close that voice is to S1. lock_threshold sets how close it must be (0-1; higher is stricter).

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Voice isolation

voice_isolation=true removes other voices before recognition (Turkish, German, French, Italian, Spanish, Russian). It switches on only after another voice is heard, so a single speaker, even in loud noise, gets the same text as without it. It does not remove noise as such; for an isolated recording use Audio isolation.

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Reference voiceprints

Without a reference, speaker lock, voice isolation and diarization take the first voice they hear as S1. Store a person’s voice once (with their consent), then name it with reference_voiceprint: S1 is that person from the first second, even if someone else speaks first. The recording is not kept. See Reference voiceprints.

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Speaker verification

Compares a recording with a stored voiceprint and answers match, uncertain or no_match, with a signed result your backend can trust.
A helper signal, not a login. It is not protected against recorded or synthetic voices. Use it together with other checks, never as the only way into an account.
See Speaker verification.

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Audio isolation

Send a recording, get it back with background voices and noise removed; the duration stays the same. For a conversation recorded in one channel send remove_voices=false, otherwise the other party is removed too. Files only. See Audio isolation.