# Speech to Text

API Overview

To simplify the integration of different **speech-to-text-transcription models (stt)**、**speech-to-text-translation models (stt)**, Infron AI provides a unified image API.

## **API Specification**

### **speech-to-text-translation models (stt)**

Translates audio into English.

{% tabs %}
{% tab title="Curl" %}

```sh
curl https://audio.onerouter.pro/v1/audio/translations \
    -H "Content-Type: multipart/form-data" \
    -H "Authorization: <API_KEY>" \
    --form 'file=@/path/to/file/speech.m4a' \
    --form 'model="whisper-1"'
```

{% endtab %}

{% tab title="Python-OpenAI-SDK" %}

```python
from openai import OpenAI
import base64
import os

client = OpenAI(
    api_key="<API_KEY>", # Replace with your Key "sk-***"
    base_url="https://audio.onerouter.pro/v1"
)

audio_file = open("/path/to/file/speech.m4a", "rb")

transcript = client.audio.translations.create(
  model="whisper-1",
  file=audio_file
)

print(transcript)
```

{% endtab %}

{% tab title="Python-HTTP" %}

```python
import os
import requests

API_URL = "https://audio.onerouter.pro/v1/audio/translations"
API_KEY = os.getenv("ONEROUTER_API_KEY")

if not API_KEY:
    raise RuntimeError("Please set the ONEROUTER_API_KEY")

file_path = os.path.join(os.path.dirname(__file__), "tts-output.mp3")

with open(file_path, "rb") as f:
    files = {"file": ("tts-output.mp3", f, "audio/mpeg")}
    data = {
        "model": "whisper-1",
        "prompt": "loudly",
        "response_format": "json",
        "temperature": 0.8,
    }
    headers = {"Authorization": API_KEY}

    response = requests.post(API_URL, headers=headers, files=files, data=data)
    response.raise_for_status()
    print(response.json())
```

{% endtab %}
{% endtabs %}

* `<API_KEY>` is your API Key generated in [API page](https://app.onerouter.pro/apiKeys).
* `model` is the model name, such as `whisper-1`, available model list can be access in [Model page](https://app.onerouter.pro/models).
* `file` is the audio file object (not file name) to transcribe, in one of these formats: `flac`, `mp3`, `mp4`, `mpeg`, `mpga`, `m4a`, `ogg`, `wav`, or `webm`.

**Example response**

```json
{
  "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
}
```

### **speech-to-text-transcription models (stt)**

Transcribes audio into the input language.

{% tabs %}
{% tab title="Curl" %}

<pre class="language-sh"><code class="lang-sh">curl https://audio.onerouter.pro/v1/speech/transcriptions \
<strong>    -H "Content-Type: multipart/form-data" \
</strong>    -H "Authorization: &#x3C;API_KEY>" \
    --form 'file=@/path/to/file/speech.m4a' \
    --form 'model="whisper-1"
</code></pre>

{% endtab %}

{% tab title="Python-OpenAI-SDK" %}

```python
from openai import OpenAI
import base64
import os

client = OpenAI(
    api_key="<API_KEY>", # Replace with your Key "sk-***"
    base_url="https://audio.onerouter.pro/v1"
)

audio_file = open("/path/to/file/speech.m4a", "rb")

transcription = client.audio.transcriptions.create(
  model="gpt-4o-transcribe",
  file=audio_file
)

print(transcription)
```

{% endtab %}

{% tab title="Python-HTTP" %}

```python
import os
import requests

API_URL = "https://audio.onerouter.pro/v1/audio/transcriptions"
API_KEY = os.getenv("ONEROUTER_API_KEY")

if not API_KEY:
    raise RuntimeError("Please set the ONEROUTER_API_KEY")

file_path = os.path.join(os.path.dirname(__file__), "tts-output.mp3")

with open(file_path, "rb") as f:
    files = {"file": ("tts-output.mp3", f, "audio/mpeg")}
    data = {
        "model": "gpt-4o-transcribe",
        "prompt": "loudly",
        "response_format": "json",
        "temperature": 0.8,
    }
    headers = {"Authorization": API_KEY}

    response = requests.post(API_URL, headers=headers, files=files, data=data)
    response.raise_for_status()
    print(response.json())
```

{% endtab %}
{% endtabs %}

* `<API_KEY>` is your API Key generated in [API page](https://app.onerouter.pro/apiKeys).
* `model` is the model name, such as `whisper-1`, available model list can be access in [Model page](https://app.onerouter.pro/models).
* `file` is the audio file object (not file name) to transcribe, in one of these formats: `flac`, `mp3`, `mp4`, `mpeg`, `mpga`, `m4a`, `ogg`, `wav`, or `webm`.

**Example response**

```json

{
  "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.",
  "usage": {
    "type": "tokens",
    "input_tokens": 14,
    "input_token_details": {
      "text_tokens": 0,
      "audio_tokens": 14
    },
    "output_tokens": 45,
    "total_tokens": 59
  }
}
```