pocket-tts is a production-ready text-to-speech library and application optimized for CPU inference. It provides a Python API, CLI (generate, serve, export-voice), and a FastAPI web server with streaming WAV output. The core architecture uses a FlowLMModel (transformer + flow matching with LSD) and a Mimi neural audio codec, with streaming inference via KV caching. It supports multiple languages (English, French, German, Portuguese, Italian, Spanish), voice cloning from audio prompts, and quantization (int8 dynamic) for efficiency. The repository also includes a full training pipeline (data preparation, alignment, tokenizer training, distributed training, distillation) and evaluation scripts. While primarily an application, the training code adds a research dimension. The codebase is modular and well-documented, with reusable components like stateful streaming modules, quantization utilities, and rotary embeddings. Some technical debt exists (deprecated quantization backend, hardcoded thread settings, multiple config versions), but overall it is a solid, actively maintained project.