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

# Speech-to-Text (STT)

> Use POST /v1/audio/transcriptions to convert speech to text

> Дата обновления: 2026-06-06

# Speech-to-Text (STT)

```
POST /v1/audio/transcriptions
```

Transcribe audio files to text, compatible with the OpenAI Whisper API format.

## Request Parameters

| Parameter         | Type   | Required | Description                                                           |
| ----------------- | ------ | -------- | --------------------------------------------------------------------- |
| `file`            | file   | Yes      | Audio file (multipart/form-data)                                      |
| `model`           | string | Yes      | Model name: `whisper-1`, `whisper-1`                                  |
| `language`        | string | No       | Audio language (ISO-639-1 format), e.g. `zh`, `en`, `ja`              |
| `response_format` | string | No       | Output format: `json` (default), `text`, `srt`, `verbose_json`, `vtt` |
| `temperature`     | number | No       | Sampling temperature, 0-1                                             |
| `prompt`          | string | No       | Prompt to help the model understand context                           |

### Supported Audio Formats

`mp3`, `mp4`, `mpeg`, `mpga`, `m4a`, `wav`, `webm`

## Request Examples

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST https://api.crazyrouter.com/v1/audio/transcriptions \
    -H "Authorization: Bearer YOUR_API_KEY" \
    -F file=@audio.mp3 \
    -F model=whisper-1 \
    -F language=en \
    -F response_format=json
  ```

  ```python Python theme={null}
  from openai import OpenAI

  client = OpenAI(
      api_key="YOUR_API_KEY",
      base_url="https://api.crazyrouter.com/v1"
  )

  with open("audio.mp3", "rb") as audio_file:
      transcript = client.audio.transcriptions.create(
          model="whisper-1",
          file=audio_file,
          language="en",
          response_format="json"
      )

  print(transcript.text)
  ```

  ```javascript Node.js theme={null}
  import OpenAI from "openai";
  import fs from "fs";

  const client = new OpenAI({
    apiKey: "YOUR_API_KEY",
    baseURL: "https://api.crazyrouter.com/v1",
  });

  const transcript = await client.audio.transcriptions.create({
    model: "whisper-1",
    file: fs.createReadStream("audio.mp3"),
    language: "en",
  });

  console.log(transcript.text);
  ```
</CodeGroup>

## Response Examples

### JSON Format

```json theme={null}
{
  "text": "Hello, welcome to the Crazyrouter API. Today we'll introduce the speech-to-text feature."
}
```

### verbose\_json Format

```json theme={null}
{
  "task": "transcribe",
  "language": "english",
  "duration": 5.2,
  "text": "Hello, welcome to the Crazyrouter API.",
  "segments": [
    {
      "id": 0,
      "start": 0.0,
      "end": 2.5,
      "text": "Hello, welcome to the Crazyrouter API."
    }
  ]
}
```

### SRT Format

```
1
00:00:00,000 --> 00:00:02,500
Hello, welcome to the Crazyrouter API.
```

***

## Audio Translation

```
POST /v1/audio/translations
```

Translate non-English audio to English text. Parameters are the same as the transcription endpoint.

```python Python theme={null}
with open("chinese_audio.mp3", "rb") as audio_file:
    translation = client.audio.translations.create(
        model="whisper-1",
        file=audio_file
    )

print(translation.text)  # Outputs English translation
```

<Note>
  Specifying the `language` parameter can improve transcription accuracy. Audio file size limit is 25MB.
</Note>