clone any voice with a 5-second audio clip. VoxCPM is an open-source project that takes a fundamentally different approach to text-to-speech. most TTS systems convert speech into discrete tokens. this creates a bottleneck that limits how natural the output can sound. VoxCPM skips tokenization entirely. it models audio in continuous space using an end-to-end diffusion autoregressive architecture. the result is speech that actually sounds human. here's what makes it special: > context-aware generation: it reads your text and infers the right prosody, emotion, and pacing automatically. no manual tuning required. > zero-shot voice cloning: give it a short audio clip, and it captures not just the voice, but accent, rhythm, and emotional tone. the model was trained on 1.8 million hours of bilingual data (English and Chinese) - supports streaming synthesis - works with both full fine-tuning and LoRA - simple Python API: `pip install voxcpm` VoxCPM1.5 runs at 44.1kHz sampling rate with 800M parameters. so this is noticeably crisper and more natural. it's Apache-2.0 licensed, so you can actually use it in production. link to the GitHub repo in the next tweet.