One-line TTS that speaks Russian, Uzbek, and Bashkir

What it does

Silero Models is a collection of pre-trained, end-to-end text-to-speech voices distributed through PyTorch Hub and a pip package. It turns text into natural-sounding speech, with a heavy emphasis on Russian and a broad catalog of CIS languages such as Kazakh, Uzbek, Armenian, and Bashkir. The project is built around portability and claims strong performance on both CPU and GPU.

The interesting bit

The real depth is in the linguistic grunt work. Russian models handle automated stress placement and homograph disambiguation—problems that break naive TTS systems—while the V5 CIS base models cover languages like Kalmyk and Moksha that rarely appear in open-source speech synthesis. SSML support is also baked into the V5 generation.

Key highlights

• Models load through PyTorch Hub or a pip package, downloading on demand.
• V5 Russian models include automated stress and homograph resolution, plus SSML markup support.
• V5 CIS base models cover roughly fifteen languages—including Azerbaijani, Kyrgyz, Tajik, and Tatar—with several offering multiple speakers.
• CIS models are released under an MIT license, while the broader project uses CC BY-NC 4.0.
• The README advertises impressive speed on both CPU and GPU.

Caveats

• The CIS base models require manual stress annotation for most languages (к+ошка), unless you use the nostress variant which only exempts non-Slavic languages—so prep work is still needed for many voices.
• Licensing is split: the CIS models are MIT, but the main project badge indicates CC BY-NC 4.0, which may complicate commercial use of non-CIS voices.
• Minimal system requirements demand a modern x86/64 processor with AVX2, which may exclude older or embedded hardware.

Verdict

Developers building voice interfaces for Russian or low-resource CIS languages should look here first; if your use case is strictly English or you need a fully permissive license for every voice, this is likely not your first stop.