• Silero Models
  • Installation and Basics
  • Text-To-Speech
    • Models and Speakers
      • V5
      • V5 CIS Base Models
      • V5 CIS Ext Models
      • V4
      • V3
    • Dependencies
    • PyTorch
    • Standalone Use
    • SSML
    • Cyrillic languages v4
    • Indic languages v4
      • Example
      • Supported languages
  • Contact
  • Licence
  • Citations
  • Further reading
    • English
    • Chinese
    • Russian

Our TTS models satisfy the following criteria:

• Fully end-to-end;
• Large library of voices;
• Natural-sounding speech;
• One-line usage, minimal, portable;
• Impressively fast on CPU and GPU;
• For the Russian language - automated stress and homographs;

You can basically use our models in 3 flavours:

• Via PyTorch Hub: torch.hub.load();
• Via pip: pip install silero and then from silero import silero_tts;
• Via caching the required models and utils manually and modifying if necessary;

Models are downloaded on demand both by pip and PyTorch Hub. If you need caching, do it manually or via invoking a necessary model once (it will be downloaded to a cache folder). Please see these docs for more information.

PyTorch Hub and pip package are based on the same code. All of the torch.hub.load examples can be used with the pip package via this basic change:

All of the provided models are listed in the models.yml file. Any metadata and newer versions will be added there.

V5 models support SSML. Also see Colab examples for main SSML tag usage.

Russian-only models support automated stress and homographs.

• All of the below models support 8000, 24000, 48000 sampling rates and contain no auto-stress or homographs;
• v5_cis_base models assume that proper stress should be added for each word for all languages, i.e. k+oshka;
• v5_cis_base_nostress models assume that proper stress should be added for each word ONLY for slavic languages (i.e. ru, bel, ukr);
• All of the below models are published under MIT licence;
• V5 UTMOS and throughput metrics;
• V5 models support SSML. Also see Colab examples for main SSML tag usage;
• Use cases for the model;
• Minimal system requirements: a PyTorch-compatible system, a modern processor with AVX2 instruction set for x86/64 platform.

• All of the below models support 8000, 24000, 48000 sampling rates and contain no auto-stress or homographs;
• v5_cis_ext models assume that proper stress should be added for each word for all languages, i.e. k+oshka;
• v5_cis_ext_nostress are coming soon;
• All of the below models are published under CC-NC-BY licence;
• V5 models support SSML. Also see Colab examples for main SSML tag usage.

V4 models support SSML. Also see Colab examples for main SSML tag usage.

V3 models support SSML. Also see Colab examples for main SSML tag usage.

Basic dependencies for Colab examples:

• torch, 1.10+ for v3 models/ 2.0+ for v4 and v5 models;
• torchaudio, latest version bound to PyTorch should work (required only because models are hosted together with STT, not required for work);
• omegaconf, latest (can be removed as well, if you do not load all of the configs);

• Standalone usage only requires PyTorch 1.12+ and the Python Standard Library;
• Please see the detailed examples in Colab;

Check out our TTS Wiki page.

To be superseded with v5 model(s) soon.

Supported tokenset: !,-.:?iuoabvgdezhziiklmnoprstufkhtschshshch'y'eiuiaiodjgjieijnjtshkjufg'g'zh'z'k'k'n'ngs'uu'kh'ch'haaaeie@zhzioouuchy

(!!!) All input sentences should be romanized to ISO format using aksharamukha. An example for hindi:

Try our models, create an issue, join our chat, email us, and read the latest news.

All of the models are published under the main repo license (i.e. CC-NC-BY) except for the base cis-tts models, which are under MIT.

• STT:

  • Towards an Imagenet Moment For Speech-To-Text - link
  • A Speech-To-Text Practitioners Criticisms of Industry and Academia - link
  • Modern Google-level STT Models Released - link

• TTS:

  • Multilingual Text-to-Speech Models for Indic Languages - link
  • Our new public speech synthesis in super-high quality, 10x faster and more stable - link
  • High-Quality Text-to-Speech Made Accessible, Simple and Fast - link

• VAD:

  • One Voice Detector to Rule Them All - link
  • Modern Portable Voice Activity Detector Released - link

• Text Enhancement:

  • We have published a model for text repunctuation and recapitalization for four languages - link

• STT:
  • Mai Xiang Yu Yin Shi Bie Ling Yu De ImageNet Shi Ke - link
  • Yu Yin Ling Yu Xue Zhu Jie He Gong Ye Jie De Qi Zong Zui - link

• STT

  • OpenAI reshili raspoznavanie rechi! Razbiraemsia tak li eto ... - link
  • Nashi servisy dlia besplatnogo raspoznavaniia rechi stali luchshe i udobnee - link
  • Telegram-bot Silero besplatno perevodit rech' v tekst - link
  • Besplatnoe raspoznavanie rechi dlia vsekh zhelaiushchikh - link
  • Poslednie obnovleniia modelei raspoznavaniia rechi iz Silero Models - link
  • Szhimaem transformery: prostye, universal'nye i prikladnye sposoby cdelat' ikh kompaktnymi i bystrymi - link
  • Ul'timativnoe sravnenie sistem raspoznavaniia rechi: Ashmanov, Google, Sber, Silero, Tinkoff, Yandex - link
  • My opublikovali sovremennye STT modeli sravnimye po kachestvu s Google - link
  • Ponizhaem bar'ery na vkhod v raspoznavanie rechi - link
  • Ogromnyi otkrytyi dataset russkoi rechi versiia 1.0 - link
  • Naskol'ko Bystroi Mozhno Sdelat' Sistemu STT? - link
  • Nasha sistema Speech-To-Text - link
  • Speech-To-Text - link

• TTS:

  • Delaem bystryi, kachestvennyi i dostupnyi sintez na iazykakh Rossii -- nuzhno vashe uchastie - link
  • My reshili zadachu omografov i udarenii v russkom iazyke - link
  • Teper' nash sintez takzhe dostupen v vide bota v Telegrame - link
  • Mozhet li sintez rechi obmanut' sistemu biometricheskoi identifikatsii? - link
  • Teper' nash sintez na 20 iazykakh - link
  • Teper' nash publichnyi sintez v super-vysokom kachestve, v 10 raz bystree i bez detskikh boliachek - link
  • Sinteziruem golos babushki, dedushki i Lenina + novosti nashego publichnogo sinteza - link
  • My sdelali nash publichnyi sintez rechi eshche luchshe - link
  • My Opublikovali Kachestvennyi, Prostoi, Dostupnyi i Bystryi Sintez Rechi - link

• VAD:

  • Novyi reliz publichnogo detektora golosa Silero VAD v6 - link
  • Nash publichnyi detektor golosa stal luchshe - link
  • A ty ispol'zuesh' VAD? Chto eto takoe i zachem on nuzhen - link
  • Modeli dlia Detektsii Rechi, Chisel i Raspoznavaniia Iazykov - link
  • My opublikovali sovremennyi Voice Activity Detector i ne tol'ko -link

• Text Enhancement:

  • Vosstanovlenie znakov punktuatsii i zaglavnykh bukv -- teper' i na dlinnykh tekstakh - link
  • My opublikovali model', rasstavliaiushchuiu znaki prepinaniia i zaglavnye bukvy v tekste na chetyrekh iazykakh - link