---
id: silero
version: "0.5.5"
license: unclear
license_treatment: permissive
maintenance: active
---

# silero — Silero Models: pre-trained enterprise-grade TTS models.

License: permissive · Maintenance: active · Downloads: 138.2K/mo

## What it is and what it does

Silero is a collection of pre-trained neural text-to-speech models designed for production use. It converts written text into natural-sounding speech across multiple languages, with particular strength in Russian (supporting automated stress and homograph resolution) and CIS region languages. The package provides end-to-end models that work on both CPU and GPU, downloadable on demand and cached locally.

You use it by loading a model for your target language and speaker, then calling apply_tts() with your text. It supports SSML markup for fine-grained control over speech characteristics. The package integrates with PyTorch and can be used either via pip or PyTorch Hub, making it portable for deployment in applications ranging from voice assistants to accessibility tools.

Use it for:

- Generate Russian speech with correct stress and homograph disambiguation for voice applications
- Build multilingual chatbots or voice interfaces supporting CIS region languages
- Create accessible audio versions of text content in supported languages
- Synthesize speech with SSML markup for prosody control in production systems
- Integrate offline TTS into applications without cloud API dependencies

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Silero provides pre-trained text-to-speech models that convert text to natural-sounding speech across multiple languages and voices, with support for SSML markup and automated stress/homograph handling for Russian.

Yes. Silero is actively maintained, has no known vulnerabilities, and offers a straightforward pip install with low friction. The permissive MIT license poses no restrictions. It's a good fit if you need multilingual TTS—especially for Russian or CIS languages—and can tolerate the PyTorch dependency. If you need English-only TTS or prefer lighter dependencies, evaluate alternatives first.

## Install

pip install silero
uv add silero
poetry add silero

## Installing silero

Before you install: Low install friction with a pure-Python wheel. Actively maintained with recent commits and no known vulnerabilities. Requires torch, omegaconf, and numpy as runtime dependencies.

License in practice: Licensed under MIT, permissive terms that allow commercial and private use with minimal restrictions.

Quickstart:

pip install silero

from silero import silero_tts
model, example_text = silero_tts(language='ru', speaker='v5_ru')
audio = model.apply_tts(text=example_text)

Requires PyTorch-compatible system with AVX2 instruction set support on x86/64 platforms; models download on first use.

Verify before relying:

- Whether V5 models support languages beyond Russian and CIS region languages listed in the excerpt
- Exact model file sizes and typical memory footprint during inference
- Whether standalone use (without PyTorch) is fully supported or requires manual setup
- Performance characteristics on CPU vs GPU for different model versions

## Package facts

- License: not declared (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 138.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

text to speech synthesis, multilingual TTS models, neural voice generation, SSML text-to-speech, Russian TTS with stress, offline speech synthesis, pre-trained TTS pytorch, text-to-speech, multilingual, pytorch-based

[View on SkillFed](https://skillfed.io/packages/silero) · [View on PyPI](https://pypi.org/project/silero/)