Fun-CosyVoice3-0.5B: open TTS that turns controllability into an interface
The third generation LLM based speech synthesis system from the FunAudioLLM group at Alibaba, 0.5B parameters, released as Fun-CosyVoice3-0.5B-2512 with base and RL weight sets plus training and inference scripts; the code repository has moved to QwenAudio/CosyVoice (Apache-2.0, 23,794 stars, verified through the GitHub API on 2026-09-29). It sits at the open source top row for speech in the audio domain, and the reason is not that it sounds most human but that it gives each of the four failure modes of production TTS an explicit interface: misread polyphonic characters go through pronunciation correction with Chinese pinyin or English CMU phonemes written straight into the input, wrong readings of numbers and symbols go through the built in text normalisation, collapsed long sentences go through RAS repetition aware sampling, and low latency goes through bidirectional streaming with an official first packet at 150ms, which is the right order of magnitude to sit inside a realtime conversational agent. Three readings matter on the metric sheet. The test-zh speaker similarity of 78.0 is the highest among 0.5B open models and above the human baseline of 75.5, yet still below the closed source Seed-TTS at 79.6, so open source first holds while world first does not. The test-hard column is the real strength, base 6.71 and RL 5.44 being the lowest in the table and better than the closed source 7.59, and hard is exactly long sentences and tongue twisters, so that lead maps to usable real scripts. English needs a discount: base test-en similarity 71.8 sits below the human baseline 73.4 and only the RL tier WER of 1.68 recovers it. Base and RL are two post training weights of one architecture, with all three error rates falling (zh CER down 33 percent, hard CER down 19 percent) and all three similarities slipping slightly, which is a good trade for broadcast and support workloads where one misread character is an incident, while voice fidelity work for a specific IP should audition the RL tier first. The repository also ships GRPO training scripts and a triton plus TensorRT-LLM runtime claimed at four times the speed of HF transformers, so post training is a path others can continue rather than a one off delivery, and the language surface covers nine languages with more than eighteen Chinese dialect accents, a tier the closed APIs still barely offer. Boundaries: the licence is two layered, Apache-2.0 for code while the weight terms live on the model pages and must be checked separately before commercial use; every reading comes from the evaluation of the authors themselves with no third party blind listening table to cross check and not recomputed here; zero shot cloning similarity comes from standard sets while real deployments depend on the noise and style of the reference recording. Graded C (vendor claim).
