snakers4/silero-models

Silero Models: pre-trained text-to-speech models made embarrassingly simple

What it solves

Silero Models provides a collection of high-quality, end-to-end text-to-speech (TTS) models that generate natural-sounding speech. It specifically addresses the need for fast, portable TTS that can run efficiently on both CPUs and GPUs, with specialized support for a wide array of languages, including Russian, Turkic, Caucasian, and various CIS languages.

How it works

The models are delivered as pre-trained weights that can be integrated into applications via PyTorch Hub, a pip package (silero), or by manually caching the models. Users can specify the language and speaker to generate audio from text. Certain models include advanced linguistic features like automated stress and homograph handling for Russian, and support for Speech Synthesis Markup Language (SSML) to control speech output.

Who it’s for

This project is for developers building voice applications, accessibility tools, or any software requiring efficient, multi-language speech synthesis without the need for heavy infrastructure.

Highlights

  • High Performance: Designed to be impressively fast on both CPU and GPU.
  • Broad Language Support: Includes specialized models for Russian, Turkic, Caucasian, and CIS languages.
  • End-to-End: Fully end-to-end architecture for simplified deployment.
  • Flexible Integration: Available via PyTorch Hub, pip, or manual caching.
  • Linguistic Precision: Features automated stress and homograph support for Russian.

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