Speech-to-Text | Venice API Docs

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.

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 file=@meeting.mp3 \
  --form model=nvidia/parakeet-tdt-0.6b-v3 \
  --form response_format=json

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.

Response Formats

Format	Use when
`json`	You want a simple `{ "text": "..." }` response.
`text`	You want plain text without JSON parsing.
`srt`	You need SubRip subtitles.
`vtt`	You need WebVTT subtitles.
`verbose_json`	You 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.

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.

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