FAQ from ChatTTS
What is ChatTTS?
ChatTTS is an open, research-backed conversational TTS framework engineered to replicate the spontaneity and expressiveness of human speech—not just read text aloud. It's purpose-built for interactive AI systems, supporting rich vocal behaviors like laughter cues, trailing-off, and emphatic repetition—all while maintaining native-level fluency in both Chinese and English.
How to use ChatTTS?
Use ChatTTS by installing its PyPI package or cloning the GitHub repo, then calling chat.infer() with your input text and optional voice parameters. No GPU required for inference—optimized for CPU and consumer-grade hardware. Prebuilt Docker images and Hugging Face Spaces demos are also available for zero-config testing.
What can ChatTTS be used for?
Beyond standard TTS applications, ChatTTS shines in scenarios demanding vocal authenticity: empathetic customer service bots, adaptive language-learning companions, AI co-hosts for live streams, and dynamic voice branding for SaaS products—all with consistent, recognizable voice identity across languages.
Does ChatTTS support multiple languages?
Yes—ChatTTS natively supports high-quality Chinese (Mandarin) and English, including cross-lingual code-switching within the same utterance. Its phoneme-aware tokenizer and bilingual acoustic modeling ensure accurate pronunciation, tone preservation (for Mandarin), and natural rhythm alignment—no fallback to generic “accented” speech.
How can developers integrate ChatTTS into their applications?
Developers can integrate ChatTTS via Python SDK, REST API (with FastAPI backend), or browser-based WebAssembly build. Full documentation covers WebSocket streaming for low-latency voice responses, batch processing for content farms, and fine-tuning pipelines for custom voice cloning—without retraining the full model.
What kind of data is used to train ChatTTS?
ChatTTS is trained on a meticulously curated corpus of ~100,000 hours of conversational speech—including spontaneous dialogues, call-center interactions, educational Q&A sessions, and scripted-but-naturalistic voiceovers—balanced across gender, age, regional accents (e.g., Beijing Mandarin, American Southern English), and speaking styles.
Is there an open-source version of ChatTTS available for developers and researchers?
Absolutely. The core ChatTTS model and training code are fully open-sourced under MIT License. A distilled, 40,000-hour variant is publicly released for reproducibility and academic use—complete with training logs, evaluation benchmarks (MOS, WER, Prosody Score), and community-contributed voice adapters.