Chatterbox is a state-of-the-art open-source text-to-speech library by Resemble AI, providing multiple TTS models (Chatterbox, Chatterbox-Multilingual, Chatterbox-Turbo, Chatterbox-Nano) and voice conversion. The architecture is modular: a T3 transformer generates speech tokens from text conditioned on speaker embeddings and optional reference audio; an S3Gen pipeline converts tokens to mel-spectrograms via conditional flow matching (CFM) and then to waveforms via a HiFiGAN vocoder. Voice cloning is achieved through a separate voice encoder (LSTM-based speaker embedding) and S3 tokenizer for prompt conditioning. The library supports 23+ languages with sophisticated multilingual tokenization (Cangjie for Chinese, hiragana for Japanese, diacritics for Hebrew, stress for Russian, Jamo decomposition for Korean). All models include imperceptible neural watermarking via Perth. The codebase is well-structured, with clean separation of concerns, efficient inference (KV caching, CFG, distilled single-step decoder for Turbo/Nano), and pinned dependencies. It is primarily an application library but includes research-grade model implementations.
MockingBird is a Chinese voice cloning system implementing the SV2TTS (Speaker Verification to Text-to-Speech) framework. It provides a complete pipeline for few-shot voice cloning: a speaker encoder extracts d-vector embeddings from reference audio, a synthesizer (Tacotron with Global Style Tokens or VITS) converts text to mel-spectrograms conditioned on the speaker embedding, and a vocoder (HiFi-GAN, Fre-GAN, or WaveRNN) generates waveforms. It also includes a PPG-based voice conversion path using a Conformer-based PPG extractor and a PPG2Mel converter. The system supports multiple Chinese datasets (aidatatang_200zh, magicdata, aishell3, data_aishell) and provides web UIs (Streamlit/FastAPI), a PyQt5 toolbox, and CLI tools for training and inference. The codebase is a fork of Real-Time-Voice-Cloning adapted for Mandarin with significant additions including VITS synthesizer, multiple vocoder options, emotion extraction via wav2vec2, and a modern web API layer. While the original author has moved to a commercial product (noiz.ai), the repository shows recent commits (2026) and maintains a large community (36k stars).