--- license: apache-2.0 pipeline_tag: text-to-speech library_name: dots_tts tags: - text-to-speech - tts - voice-cloning - flow-matching - meanflow - one-step --- # dots.tts-mf-1step

GitHub Playground Demo Page

This repository provides a standalone dots.tts artifact for **fixed one-step inference**. The sampling contract is stored in `config.json` and selected automatically. Sampling options should be omitted. ## Quick start Install dots.tts from its official repository, then load this artifact exactly like a standard dots.tts model: ```python from dots_tts.runtime import DotsTtsRuntime import soundfile as sf runtime = DotsTtsRuntime.from_pretrained( "dots-studio/dots.tts-mf-1step", precision="bfloat16", ) result = runtime.generate( text="Hello, this is a one-step synthesis test.", prompt_audio_path="reference.wav", prompt_text="The exact transcript of the reference audio.", ) sf.write("output.wav", result["audio"].float().cpu().squeeze().numpy(), result["sample_rate"]) ``` ## Scope and limitations This model was optimized for the fixed one-step path. Multi-step quality is not claimed. A fresh public benchmark evaluation is not included in this artifact. High-fidelity voice cloning must be used only with authorization and consent; do not use it for impersonation, fraud, or disinformation. --- ## Citation ```bibtex @article{dotstts2026, title = {dots.tts Technical Report}, author = {dots.tts Team}, year = {2026}, eprint = {2606.07080}, archivePrefix = {arXiv}, primaryClass = {cs.SD}, } ``` ## License Released under [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0).