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Silero Models
Silero Models is a collection of end-to-end text-to-speech models that generate natural-sounding speech and support various languages and SSML tags.
Silero Models provides a set of pre-trained, end-to-end text-to-speech models designed for natural-sounding speech generation. The library supports a wide array of speakers and languages, including Russian, various Turkic, Caucasian, and other CIS languages. Users can implement the models via PyTorch Hub or through the pip package manager, with support for SSML tags to control speech characteristics. These models are built to operate efficiently on both CPU and GPU hardware, requiring only a modern processor with an AVX2 instruction set for x86/64 platforms. The project offers multiple versions, some of which feature automated stress and homograph support for Russian, while others require manual stress labeling.
Silero Models at a glance
Key features
- End-to-end speech synthesis
- Large library of unique voices
- SSML tag support for fine-tuned output
- Fast execution on CPU and GPU hardware
- Automated stress and homograph handling for Russian
- Support for 8000, 24000, and 48000 sampling rates
- Multiple language support including Turkic, Caucasian, and CIS groups
Use it for
- Text-to-speech application development
- Speech synthesis for digital content
- Audio generation for automated systems
Alternatives to Silero Models
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- audio.cpp — Runs modern audio models locally with high-performance, native C++ execution.
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- FireRedAudio — A unified model handling understanding and generation with decoupled continuous representations.
- MLX Audio — It enables fast audio model inference directly on Apple M-series chips.
- Kokoro-FastAPI — Generate hours of high quality speech with an OpenAI-compatible endpoint.
- transcribe.cpp — Runs 16 model families and 60+ variants with GPU and CPU acceleration.
- AuK — It handles zero-shot TTS, editing, and enhancement via natural language.
- Speech-to-Speech — Fully modular, swappable components with local or hosted execution options.
- Piper — Runs locally and offers fast neural text-to-speech synthesis.
- Ema Lightning — It runs locally on your GPU or CPU with high accuracy and extreme speed.
- ESPnet — Provides reproducible recipes and hundreds of pretrained models for various speech tasks.
All Silero Models alternatives