Skip to content

Latest commit

 

History

History
271 lines (197 loc) · 12 KB

changelog.md

File metadata and controls

271 lines (197 loc) · 12 KB
Raw

Plans

Updates

2022-06-06 Silero TTS in 20 Languages With 174 Speakers

  • Huge release - 20 languages, 173 voices;
  • 1 new high quality Russian voice (eugeny);
  • The CIS languages: Kalmyk, Russian, Tatar, Uzbek и Ukrainian;
  • Romance and Germanic languages: English, Indic English, Spanish, German, French;
  • 10 Indic languages;
  • Russian automated stress model vastly improved (please see this link for details);
  • All models inherit all of the previous SSML perks;

2022-04-12 Silero TTS in High Resolution, 10x Faster and More Stable

  • Huge release - Russian only for now;
  • Model size reduced 2x;
  • New models are 10x faster;
  • We added flags to control stress;
  • Now the models can make proper pauses;
  • High quality voice added (and unlimited "random" voices);
  • All speakers squeezed into the same model;
  • Input length limitations lifted, now models can work with paragraphs of text;
  • Pauses, speed and pitch can be controlled via SSML;
  • Sampling rates of 8, 24 or 48 kHz are supported;
  • Models are much more stable — they do not omit words anymore;

2022-02-28 Experimental Pip Package

  • 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. Hence all examples, historically based on torch.hub.load can be used with a pip-package;

2022-02-24 English V6 Release

  • New en_v6 models;
  • Quality improvements for English models;

2021-12-09 Improved Text Recapitalization and Repunctuation Model for 4 Languages

  • The model now can work with long inputs, 512 tokens or ca. 150 words;
  • Inputs longer than 150 words are automatically processed in chunks;
  • The bugs with newer PyTorch versions have been fixed;
  • Model was trained longer with larger batches;
  • Model size slightly reduced to 85 MB;
  • The rest of model optimizations were deemed too high maintenance;

2021-10-06 Text Recapitalization and Repunctuation Model for 4 Languages

  • Inserts capital letters and basic punctuation marks (dot, comma, hyphen, question mark, exclamation mark, dash for Russian);
  • Works for 4 languages (Russian, English, German, Spanish) and can be extended;
  • By design is domain agnostic and is not based on any hard-coded rules;
  • Has non-trivial metrics and succeeds in the task of improving text readability;

2021-09-03 German V4 and English V5 Models

  • German V4 large jit and onnx models;
  • English V5 small (jit and onnx), small_q (only jit) and xlarge (jit and onnx) models;
  • Vast quality improvements (metrics to be added shortly) on the majority of domains;
  • English xsmall models coming soon (jit and onnx);

2021-08-09 German V3 Large Model

  • German V3 Large jit model trained on more data - large quality improvement;
  • Metrics coming soon;

2021-06-18 Large V2 TTS release, v4_0 Large English STT Model

  • Added v4_0 large English model with metrics;
  • V2 TTS models with x4 faster vocoder;
  • Russian models now feature automatic stress and ё, homonyms are not handled yet;
  • A multi-language multi-speaker model;

2021-04-21 Large V2 TTS release, v4_0 Large English STT Model

Huge update for English!

  • Polish docs;
  • Add xsmall and xsmall_q model flavours for en_v3;
  • Polish performance benchmarks page a bit;

2021-04-20 Add v3 STT English Models

Huge update for English!

  • Default model (jit or onnx) size is reduced almost by 50% without sacrificing quality (!);
  • New model flavours: jit_q (smaller quantized model), jit_skip (with exposed skip connections), jit_large (higher quality model), onnx_large (!);
  • New smallest model jit_q is only 40M in size (!);
  • Tensorflow checkpoints discontinued;
  • New performance benchmarks - default models are on par with previous models and Google, large models mostly outperform Google (!);
  • Even more quality improvements coming soon (!);
  • CE benchmarks coming soon;
  • xsmall model was created (2x smaller than the default), but I could not quantize it. I am looking into creating a xxsmall model;
  • Still working on making EE models fully JIT-traceable;

2021-03-29 Add v1 TTS Models

2021-03-03 Add xxsmall Speed Metrics

  • See metrics here
  • Note that this is only an acoustic model, full end-to-end system metrics differ, though xxsmall metrics trickle down for CPU systems

2021-03-03 Ukrainian Model V3 Released

  • Fine tuned from a commercial production Russian model
  • Trained on a larger corpus (around 1,000 hours)
  • Model flavors: jit (CPU or GPU), jit_q (quantized and CPU only) and onnx (ONNX)
  • Huge model speed improvements for CPU inference (!roughly 3x faster!) compared to the previous one, comparable with xxsmall from here
  • Will be dropping TF support altogether
  • No proper quality benchmarks for an experimental model though

2021-02-15 Some Organizational Issues

  • Migrate to our own model hosting
  • Solve large parasite traffic / DDOS issue, source still unknown
  • Remove the CDN
  • Some community / answers tidying up
  • Major progress on silero-vad
  • Major progress on TTS, preparing for a release

2020-12-04 Add EE Distro Sizing and New Speed Metrics

2020-11-26 Fix TensorFlow Examples

2020-11-03 [Experimental] Ukrainian Model V1 Released

  • An experimental model
  • Trained from a small community contributed corpus
  • New Full model size reduced to 85 MB
  • New - quantized model is ony 25 MB
  • No TF or ONNX models
  • Will be re-released a fine-tuned model from a larger Russian corpus upon V3 release

2020-11-03 English Model V2 Released

  • A minor release, i.e. other models not affected
  • English model was made much more robust to certain dialects
  • Performance metrics coming soon

2020-10-28 Minor PyTorch 1.7 fix

  • torch.hub.load signature was changed

2020-10-19 Update wiki

2020-10-03 Batched ONNX and TF Models

  • Extensively clean up and simplify ONNX and TF model code
  • Add batch support to TF and ONNX models
  • Update examples
  • (pending) Submit new models to TF Hub and update examples there

2020-09-29 Update English benchmarks

new pruned double-lm quality benchmarks

2020-09-29 Published on TF Hub

2020-09-28 Added Timestamps To Decoder

  • Now standard decoder has an option to return word timestamps
  • Please see Colab examples for PyTorch

2020-09-27 Examples, Usability, TF Example

  • Polish and simplify the main readme
  • Remove folders from inside of TF archives
  • Polish model url naming, purge CDN cache
  • Add TF Colab example
  • Remove old ONNX example
  • Submit to TF and ONNX hub

2020-09-23 Fixed broken TF Model Archives

  • Fixed weird archiving issue for Windows, purged CDN cache

2020-09-23 Silero Models now on Torch Hub

2020-09-22 Tensorflow SavedModels, Colab VAD, tf.js

  • Add VAD to colab example
  • Add proper SavedModel Tensorflow checkpoints for all of the languages
  • Add experimental tf.js checkpoints for English

2020-09-19 Fx Minor Bugs

Fix minor colab bugs

2020-09-17 TorchHub

  • Added loading via TorchHub
  • Added issue templates
  • Fix typos

2020-09-16 V1 Release

  • Examples and docs further polished
  • Added a more thorough colab example with file upload / speech recording
  • Added performance benchmarks
  • Added quality benchmarks for Spanish in the wiki

2020-09-15 Quality Benchmarks for German

Added quality benchmarks for German in the wiki

2020-09-12 Quality Benchmarks for English

Added quality benchmarks for English in the wiki

2020-09-11 Initial upload

First commit and first models uploaded:

  • English
  • German
  • Spanish