> ## Documentation Index
> Fetch the complete documentation index at: https://docs.deepinfra.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Speech Recognition

> Transcribe audio to text using Whisper and other speech recognition models.

DeepInfra hosts [Whisper](https://github.com/openai/whisper) and other speech recognition models. Given an audio file, they produce transcribed text with per-sentence timestamps.

Browse [all speech recognition models](https://deepinfra.com/models/automatic-speech-recognition).

## Models

* `openai/whisper-large` — best accuracy
* `openai/whisper-medium`, `openai/whisper-small`, `openai/whisper-base` — faster, lighter
* `openai/whisper-timestamped-medium` — per-word timestamp segmentation

## Example

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST \
      -H "Authorization: Bearer $DEEPINFRA_TOKEN" \
      -F audio=@audio.mp3 \
      'https://api.deepinfra.com/v1/inference/openai/whisper-large'
  ```

  ```javascript JavaScript theme={null}
  import { AutomaticSpeechRecognition } from "deepinfra";
  import path from "path";
  import { fileURLToPath } from "url";

  const __filename = fileURLToPath(import.meta.url);
  const __dirname = path.dirname(__filename);

  const DEEPINFRA_API_KEY = "$DEEPINFRA_TOKEN";
  const MODEL = "openai/whisper-large";

  const client = new AutomaticSpeechRecognition(MODEL, DEEPINFRA_API_KEY);

  const input = {
    audio: path.join(__dirname, "audio.mp3"),
  };
  const response = await client.generate(input);
  console.log(response.text);
  ```
</CodeGroup>

## Supported audio formats

* `mp3`
* `wav`

## Response

```json theme={null}
{
  "text": "Hello, this is a transcription of the audio file.",
  "segments": [
    {
      "start": 0.0,
      "end": 3.5,
      "text": "Hello, this is a transcription of the audio file."
    }
  ]
}
```

## Additional parameters

Each model exposes different parameters (language, task, etc.). Check the model's API documentation page for details.

## Tutorial

See the [Whisper tutorial](/tutorials/whisper) for a complete walkthrough.