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Paper · arXiv

dots.tts Technical Report

We present dots$.$tts, a 2B-parameter continuous autoregressive text-to-speech (TTS) foundation model that models speech in a continuous latent space. Compared with existing continuous autoregressive models, our key innovations are threefold. First, we train an AudioVAE with multiple objectives to build a semantically structured and prediction-friendly continuous speech space. Second, we use full-history conditioning in the flow-matching head to preserve long-range consistency and reduce drift during generation. Third, we apply reward-free self-corrective post-training to the flow-matching head to further improve robustness and acoustic quality. After being trained on a large-scale multil...

AuthorsShi Lian, Changtao Li, Bohan Li et al.
Primary categorycs.SD
Published5 June 2026
Last updated at source10 August 2026
cs.SDcs.AIeess.AS
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