README.md

metadata

title: Soprano TTS API
emoji: 🎤
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: apache-2.0
app_port: 7860

Soprano TTS API Space

This Hugging Face Space provides a REST API for the Soprano Text-to-Speech model loaded from Gaston895/aegis001. Soprano is an ultra-lightweight, on-device TTS model designed for expressive, high-fidelity speech synthesis.

Model Source

This space automatically loads the Soprano TTS model from the Hugging Face repository:

• Repository: Gaston895/aegis001
• Model Type: Qwen3ForCausalLM optimized for text-to-speech
• Parameters: 80M parameters
• Architecture: Ultra-lightweight design for CPU inference

Features

• Ultra-fast generation: Optimized for CPU inference on Hugging Face Spaces
• Low memory usage: <1GB memory footprint
• High quality: Crystal clear 32kHz audio generation
• REST API: Easy integration with any application
• Automatic model loading: Downloads model from HF repository on startup

API Endpoints

Health Check

GET /health

Single Text Synthesis

POST /synthesize
Content-Type: application/json

{
  "text": "Hello, this is Soprano TTS speaking!",
  "temperature": 0.7,
  "top_p": 0.9,
  "format": "wav"
}

Batch Text Synthesis

POST /batch_synthesize
Content-Type: application/json

{
  "texts": [
    "First sentence to synthesize.",
    "Second sentence to synthesize."
  ],
  "temperature": 0.7,
  "top_p": 0.9
}

Parameters

• text (required): Text to synthesize
• temperature (optional): Controls randomness (0.1-2.0, default: 0.7)
• top_p (optional): Controls diversity (0.1-1.0, default: 0.9)
• format (optional): Output format - "wav" or "base64" (default: "wav")

Response Formats

WAV File Response

Returns audio file directly for download.

Base64 Response

{
  "success": true,
  "audio_base64": "UklGRiQAAABXQVZFZm10...",
  "sample_rate": 32000,
  "duration": 2.5,
  "text": "Input text"
}

Usage Examples

cURL

# Synthesize text and save as WAV
curl -X POST https://huggingface.co/spaces/Gaston895/aegis001/synthesize \
  -H "Content-Type: application/json" \
  -d '{"text": "Hello world!", "format": "wav"}' \
  --output speech.wav

# Get base64 encoded audio
curl -X POST https://huggingface.co/spaces/Gaston895/aegis001/synthesize \
  -H "Content-Type: application/json" \
  -d '{"text": "Hello world!", "format": "base64"}'

Python

import requests
import base64

# Synthesize speech
response = requests.post(
    "https://huggingface.co/spaces/Gaston895/aegis001/synthesize",
    json={
        "text": "Hello, this is Soprano TTS!",
        "temperature": 0.7,
        "format": "base64"
    }
)

if response.status_code == 200:
    data = response.json()
    audio_data = base64.b64decode(data['audio_base64'])
    
    with open('output.wav', 'wb') as f:
        f.write(audio_data)

JavaScript

const synthesizeText = async (text) => {
  const response = await fetch('https://huggingface.co/spaces/Gaston895/aegis001/synthesize', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      text: text,
      format: 'base64'
    })
  });
  
  const data = await response.json();
  return data.audio_base64;
};

Model Information

This space uses the Soprano TTS model from Gaston895/aegis001, which features:

• Architecture: Qwen3ForCausalLM
• Parameters: 80M
• Context Length: 1024 tokens
• Vocabulary Size: 8192
• Audio Quality: 32kHz sampling rate
• Optimization: CPU-optimized for Hugging Face Spaces

Deployment

The model is automatically downloaded from the Hugging Face repository when the space starts up. No manual model files are needed in the space repository.

Limitations

• English-only support
• No voice cloning capabilities
• Occasional mispronunciation of uncommon words
• CPU-optimized for Hugging Face Spaces
• Model loading time on first startup (~1-2 minutes)

License

This project is licensed under the Apache-2.0 license.