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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.

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Basic Usage

import os

import requests

with open("meeting.mp3", "rb") as audio:
    response = requests.post(
        "https://api.venice.ai/api/v1/audio/transcriptions",
        headers={"Authorization": f"Bearer {os.environ['VENICE_API_KEY']}"},
        files={"file": audio},
        data={
            "model": "nvidia/parakeet-tdt-0.6b-v3",
            "response_format": "json",
        },
    )

response.raise_for_status()
print(response.json()["text"])

import { createReadStream } from "node:fs";
import FormData from "form-data";

const form = new FormData();
form.append("file", createReadStream("meeting.mp3"));
form.append("model", "nvidia/parakeet-tdt-0.6b-v3");
form.append("response_format", "json");

const response = await fetch("https://api.venice.ai/api/v1/audio/transcriptions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.VENICE_API_KEY}`,
    ...form.getHeaders(),
  },
  body: form,
});

if (!response.ok) {
  throw new Error(await response.text());
}

const transcript = await response.json();
console.log(transcript.text);

curl https://api.venice.ai/api/v1/audio/transcriptions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  --form [email protected] \
  --form model=nvidia/parakeet-tdt-0.6b-v3 \
  --form response_format=json

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Supported Inputs

Common audio formats include mp3, mp4, mpeg, mpga, m4a, wav, webm, flac, and ogg. See the Speech-to-Text Models page for current model support and pricing.

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Response Formats

FormatUse when
jsonYou want a simple { "text": "..." } response.
textYou want plain text without JSON parsing.
srtYou need SubRip subtitles.
vttYou need WebVTT subtitles.
verbose_jsonYou need richer timestamp and segment metadata.
Use subtitle formats when the transcript will be paired with media playback. Use json or text when the transcript feeds summarization, search, or downstream chat prompts.

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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.