Transcription

Transcription is an experimental feature.

The AI SDK provides the transcribe function to transcribe audio using a transcription model.

import { experimental_transcribe as transcribe } from 'ai';
import { openai } from '@ai-sdk/openai';
import { readFile } from 'fs/promises';

const transcript = await transcribe({
  model: openai.transcription('whisper-1'),
  audio: await readFile('audio.mp3'),
});

The audio property can be a Uint8Array, ArrayBuffer, Buffer, string (base64 encoded audio data), or a URL.

To access the generated transcript:

const text = transcript.text; // transcript text e.g. "Hello, world!"
const segments = transcript.segments; // array of segments with start and end times, if available
const language = transcript.language; // language of the transcript e.g. "en", if available
const durationInSeconds = transcript.durationInSeconds; // duration of the transcript in seconds, if available

Settings

Provider-Specific settings

Transcription models often have provider or model-specific settings which you can set using the providerOptions parameter.

import { experimental_transcribe as transcribe } from 'ai';
import { openai } from '@ai-sdk/openai';
import { readFile } from 'fs/promises';

const transcript = await transcribe({
  model: openai.transcription('whisper-1'),
  audio: await readFile('audio.mp3'),
  providerOptions: {
    openai: {
      timestampGranularities: ['word'],
    },
  },
});

Abort Signals and Timeouts

transcribe accepts an optional abortSignal parameter of type AbortSignal that you can use to abort the transcription process or set a timeout.

import { openai } from '@ai-sdk/openai';
import { experimental_transcribe as transcribe } from 'ai';
import { readFile } from 'fs/promises';

const transcript = await transcribe({
  model: openai.transcription('whisper-1'),
  audio: await readFile('audio.mp3'),
  abortSignal: AbortSignal.timeout(1000), // Abort after 1 second
});

Custom Headers

transcribe accepts an optional headers parameter of type Record<string, string> that you can use to add custom headers to the transcription request.

import { openai } from '@ai-sdk/openai';
import { experimental_transcribe as transcribe } from 'ai';
import { readFile } from 'fs/promises';

const transcript = await transcribe({
  model: openai.transcription('whisper-1'),
  audio: await readFile('audio.mp3'),
  headers: { 'X-Custom-Header': 'custom-value' },
});

Warnings

Warnings (e.g. unsupported parameters) are available on the warnings property.

import { openai } from '@ai-sdk/openai';
import { experimental_transcribe as transcribe } from 'ai';
import { readFile } from 'fs/promises';

const transcript = await transcribe({
  model: openai.transcription('whisper-1'),
  audio: await readFile('audio.mp3'),
});

const warnings = transcript.warnings;

Error Handling

When transcribe cannot generate a valid transcript, it throws a AI_NoTranscriptGeneratedError.

This error can arise for any the following reasons:

The model failed to generate a response
The model generated a response that could not be parsed

The error preserves the following information to help you log the issue:

responses: Metadata about the transcription model responses, including timestamp, model, and headers.
cause: The cause of the error. You can use this for more detailed error handling.

import {
  experimental_transcribe as transcribe,
  NoTranscriptGeneratedError,
} from 'ai';
import { openai } from '@ai-sdk/openai';
import { readFile } from 'fs/promises';

try {
  await transcribe({
    model: openai.transcription('whisper-1'),
    audio: await readFile('audio.mp3'),
  });
} catch (error) {
  if (NoTranscriptGeneratedError.isInstance(error)) {
    console.log('NoTranscriptGeneratedError');
    console.log('Cause:', error.cause);
    console.log('Responses:', error.responses);
  }
}

Transcription Models

Provider	Model
OpenAI	`whisper-1`
OpenAI	`gpt-4o-transcribe`
OpenAI	`gpt-4o-mini-transcribe`
ElevenLabs	`scribe_v1`
ElevenLabs	`scribe_v1_experimental`
Groq	`whisper-large-v3-turbo`
Groq	`distil-whisper-large-v3-en`
Groq	`whisper-large-v3`
Azure OpenAI	`whisper-1`
Azure OpenAI	`gpt-4o-transcribe`
Azure OpenAI	`gpt-4o-mini-transcribe`
Rev.ai	`machine`
Rev.ai	`low_cost`
Rev.ai	`fusion`
Deepgram	`base` (+ variants)
Deepgram	`enhanced` (+ variants)
Deepgram	`nova` (+ variants)
Deepgram	`nova-2` (+ variants)
Deepgram	`nova-3` (+ variants)
Gladia	`default`
AssemblyAI	`best`
AssemblyAI	`nano`
Fal	`whisper`
Fal	`wizper`

Above are a small subset of the transcription models supported by the AI SDK providers. For more, see the respective provider documentation.