> ## 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.

# Python Audio

> Python text-to-speech (TTS) and speech-to-text (STT)

> Last updated: 2026-06-06

## Text-to-Speech (TTS)

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

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

# Generate speech
response = client.audio.speech.create(
    model="tts-1",
    voice="alloy",
    input="Hello, welcome to the Crazyrouter API service."
)

# Save as MP3 file
response.stream_to_file("output.mp3")
print("Audio saved to output.mp3")
```

### Available Voices

| Voice     | Characteristics   |
| --------- | ----------------- |
| `alloy`   | Neutral, balanced |
| `echo`    | Male, calm        |
| `fable`   | Male, warm        |
| `onyx`    | Male, deep        |
| `nova`    | Female, lively    |
| `shimmer` | Female, soft      |

### High Quality TTS

```python theme={null}
# Use tts-1-hd for higher audio quality
response = client.audio.speech.create(
    model="tts-1-hd-1106",
    voice="nova",
    input="High quality speech synthesis example",
    response_format="opus",  # Supports mp3, opus, aac, flac
    speed=1.0  # 0.25 to 4.0
)

response.stream_to_file("output_hd.opus")
```

## Speech-to-Text (STT)

```python theme={null}
# Whisper speech recognition
audio_file = open("recording.mp3", "rb")

transcript = client.audio.transcriptions.create(
    model="whisper-1",
    file=audio_file,
    language="en"  # Optional, specifying language improves accuracy
)

print(transcript.text)
```

### Transcription with Timestamps

```python theme={null}
transcript = client.audio.transcriptions.create(
    model="whisper-1",
    file=open("recording.mp3", "rb"),
    response_format="verbose_json",
    timestamp_granularities=["segment"]
)

for segment in transcript.segments:
    print(f"[{segment['start']:.1f}s - {segment['end']:.1f}s] {segment['text']}")
```

## Audio Translation

Translate non-English audio to English text:

```python theme={null}
audio_file = open("foreign_audio.mp3", "rb")

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

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

<Note>
  TTS supported models include `tts-1`, `tts-1-hd-1106`, and `tts-1`. STT uses the `whisper-1` model.
</Note>