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Speech-to-text transcribes spoken audio into written text. Send an audio file to /audio/transcriptions, choose a transcription model, and select the response format you want back. Working with a recording of a conversation? Meeting Notes with Speech to Text goes from an audio file to decisions and action items that cite the second they were agreed, including which models return segment timings and how to handle a transcript that never says who is speaking.

Basic Usage

Supported Inputs

Supported audio formats are wav, wave, flac, m4a, aac, mp4, mp3, ogg, oga, and webm. A file is accepted when either its MIME type or its extension is on that list, and the uploaded bytes must also pass a magic-byte check — renaming a file to a supported extension will not get it through. See the Speech-to-Text Models page for current model support and pricing.

Response Formats

These are the only two values response_format accepts. There is no srt, vtt, or verbose_json option — requesting one returns a 400. To build subtitles, use timestamps: true with response_format: json and render the timing data yourself.

Timestamps

Pass timestamps=true to get timing data back alongside the transcript. Support is model-specific, and the granularity differs:
The default model, nvidia/parakeet-tdt-0.6b-v3, accepts timestamps=true and then ignores it — you get a response containing only text, with no error and no warning. Pick a model from the table above if you need timings, and check that the timestamps key exists before reading it.
Segment-level models return a segment array instead, where each entry is { "text": "...", "start": 0.0, "end": 3.2 }. All times are in seconds.
No Venice transcription model performs speaker diarization, so there is no speaker field on any response. A transcript is a single stream of text — speakers can only be attributed when a name is said out loud.

Production Tips

  • Keep audio clear and avoid overlapping speakers when possible.
  • Split very long recordings into smaller chunks if your workflow needs lower latency or easier retries.
  • Store the original audio path, model ID, and response format with each transcript for auditability.