The Claire Speech Engine (CSE)

The Claire Speech Engine is a production-grade, backend-agnostic speech synthesis library built in Python.

Installation

pip install claire-speech-engine

To install from source for development:

git clone https://github.com/Yukariii04/Claire-Speech-Engine.git
cd Claire-Speech-Engine
pip install -e ".[dev]"

Quick Start

1. Setup Your Backend

Because CSE is backend-agnostic, the core framework does not ship with heavy ML dependencies. You choose the backend you want and install its specific requirements.

Currently, CSE officially supports the following backends on Python 3.12+:

• Kokoro
• StyleTTS2

Use the built-in setup tools to automatically download models and install all required ML dependencies for your chosen backend:

# Install dependencies and download models for Kokoro
cse setup kokoro

# Install dependencies and download models for StyleTTS2
cse setup styletts2

2. Examples

You can instantly scaffold a runnable example into your current directory to test your setup:

cse example kokoro
python example_kokoro.py

3. Check Backend Health

You can view a real-time dashboard of your installed backends, their status, and their voice counts:

cse backends

4. Interactive CLI

# List available voices across all backends
cse voices

# Interactively select your default backend and voice
cse voice

5. Python API

from cse import SpeechEngine

engine = SpeechEngine()
# Loads your saved CLI preference, or falls back to backend default
engine.load_voice()

speech = engine.speak("Synthesis is now extremely simple.")
if speech.success:
    print(f"Audio saved to: {speech.audio_path}")

Architecture & Vision

Read these documents to understand the core philosophy and design of the engine:

• Project Vision Document (PVD-001)
• Architecture Overview

Roadmap

The Claire Speech Engine (CSE) is currently at v1.0.4. The core framework is now feature-frozen to ensure a stable foundation.

Future development will transition to:

1. CPE (Claire Performance Engine): Prosody, emotion, and dialogue planning.
2. CSM (Claire Speech Model): Core acoustic ML model training.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Development

Running Tests

pytest tests/

Running Benchmarks

pytest tests/golden/test_perf_golden.py

See docs/Benchmarks/README.md for full performance targets and reports.