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PyPI · #4009 most downloaded on PyPI
All-in-one speech toolkit in pure Python and Pytorch
Last release 1 months ago
27 Aug 2026
Ships fairly regularly
a new release about every 5 months
Most releases are documented
notes for 16 of 19 stable releases
Nothing withdrawn
no release was ever pulled
6 years old
19 releases · first in 2021
One column per quarter.
[ da704dd ]: FocalCodec-Stream [ICASSP 2026] ( #3050 ) (Luca Della Libera) #3050
Remove deprecated abstractproperty (from Samsung, AI Center, Cambridge) by @rogiervd in #2915
This major release extends SpeechBrain's support for SpeechLLMs and introduces several new features, recipes, and improvements.
Along with internal improvements and bug fixes. Here follows a changelog of the main changes (omitting some minor bugfixes):
Full Changelog: v1.0.3...v1.1.0
self.device for AMP by @Adel-Moumen in #2882FetchConfig for standardizing use of fetch by @pplantinga in #2828Note truncated.
Add People's Speech (30,000 hours) Conformer ASR (Code from Samsung AI Center Cambridge) by @TParcollet in #2767
Full Changelog: v1.0.2...v1.0.3
This is a minor update which includes some new features and recipes, internal improvements, bugfixes and improved tutorials.
This is a minor update which includes some new features and recipes, internal improvements, bugfixes and improved tutorials.
Here follows a changelog of the main changes (omitting some minor bugfixes):
fetch and Pretrained, greatly reducing the use of symlinks out of the box as much as possible (see down below)seed_everything, improved DDP handling for seeding (#2654)fetching semanticsWe have made a number of changes that affect how fetch works, and this affects various things in a way you should be aware of.
from_hparams, the savedir refers to the directory where files should be collected. It is now optional and defaults to None.
savedir.savedir, behavior should be largely unchanged (although more robust).fetch_strategy.
savedir. For instance, if some model file is available in HuggingFace cache, you can now choose between copying, symlinking or not linking the file in the savedir.fetch now has an allow_network parameter, which defaults to True. When disabled, this fails if the URI is not available locally, or if the file isn't found locally in HF cache.fetch also now has an allow_updates parameter, which defaults to True. It interrogates HF even if a local path is present in order to update any model files (or switch revisions), if required.This is a minor update which includes some new features and recipes, internal improvements, bugfixes, compatibility improvements, and wider Python bac
This is a minor update which includes some new features and recipes, internal improvements, bugfixes, compatibility improvements, and wider Python backwards compatibility.
NOTE: both v1.0.0 and v1.0.1 were released earlier than this date on GitHub. These releases were accidentally marked as drafts.
3.8 to 3.12 (instead of 3.9-3.11) and improved our testing in that regard.speechbrain.pretrained imports that were broken following a v1.0 refactor (#2485)ctc_segmentation (#2505)RelPosEncXL (#2498)--editable flag (#2541)causal in TransformerASR (#2606)People familiar with SpeechBrain know very well that we do our best to avoid backward incompatible changes. While SpeechBrain has consistently priorit…
Please, help our community project. Star on GitHub!
📅 On February 2024, we released SpeechBrain 1.0, the result of a year-long collaborative effort by a large international network of developers led by our exceptional core development team.
SpeechBrain 1.0 introduces significant advancements, expanding support for diverse datasets and tasks, including NLP and EEG processing.
The toolkit now excels in Conversational AI and various sequence processing applications.
Improvements encompass key techniques in speech recognition, streamable conformer transducers, integration with K2 for Finite State Transducers, CTC decoding and n-gram rescoring, new CTC/joint attention Beam Search interface, enhanced compatibility with HuggingFace Models (including GPT2 and Llama2), and refined data augmentation, training, and inference processes.
We have created a new repository dedicated to benchmarks, accessible at here. At present, this repository features benchmarks for various domains, including speech self-supervised models (MP3S), continual learning (CL-MASR), and EEG processing (SpeechBrain-MOABB).
For detailed technical information, please refer to the section below.
People familiar with SpeechBrain know very well that we do our best to avoid backward incompatible changes. While SpeechBrain has consistently prioritized maintaining backward compatibility, the introduction of this new major version presented an opportunity for significant enhancements and refactorings.
🤗 HuggingFace Interface Refactor:
🔍 BeamSearch Refactor:
🎨 Data Augmentation Refactor:
🧠 Brain Class Refactor:
🔍 Inference Interfaces Refactor:
python train.py hparams/config.yaml --profile_training --profile_warmup 10 --profile_steps 5Release of a new benchmark repository, aimed at aiding the community in standardization across various areas.
A benchmark designed to assess continual learning techniques on multilingual speech recognition tasks
Provides scripts to train multilingual ASR systems, specifically Whisper and WavLM-based, on a subset of 20 languages selected from Common Voice 13 in a continual learning fashion.
Implementation of various methods, including rehearsal-based, architecture-based, and regularization-based approaches.
Full Changelog: v0.5.16...v1.0.0
…a seamless transition to SpeechBrain 1.0 where backward incompatible modifications will take place.
SpeechBrain 0.5.16 will be the last minor version of SpeechBrain before the major release of SpeechBrain 1.0.
In this minor version, we have focused on refining the existing features without introducing any interface changes, ensuring a seamless transition to SpeechBrain 1.0 where backward incompatible modifications will take place.
Key Highlights of SpeechBrain 0.5.16:
Bug Fixes: Numerous small fixes have been implemented to enhance the overall stability and performance of SpeechBrain.
Testing and Documentation: We have dedicated efforts to improve our testing infrastructure and documentation, ensuring a more robust and user-friendly experience.
Expanded Model and Dataset Support: SpeechBrain 0.5.16 introduces support for several new models and datasets, enhancing the versatility of the platform. For a detailed list, please refer to the commits below.
Stay informed and get ready for the groundbreaking SpeechBrain 1.0, where we will unveil substantial changes and exciting new features.
Thank you for being a part of the SpeechBrain community!
Note truncated.
SpeechBrain 0.5.15 Release Notes
We are thrilled to announce the release of SpeechBrain version 0.5.15! This new version represents a significant step forward for our open-source Conversational AI toolkit. The core team, along with a rapidly growing network of contributors, has worked diligently to enhance and expand the toolkit while addressing various issues.
This release marks a crucial point as it will likely be the final minor version before the highly anticipated SpeechBrain 1.0, scheduled for release in the coming months. We have achieved notable milestones in this version, and a summary of the key achievements is presented below. For a comprehensive list of all changes, please refer to the detailed notes at the end.
Benchmark Repository:
We are proud to introduce the benchmark repository, which aims to provide a standard recipe for researchers to benchmark and compare different techniques and models. Currently, the following benchmarks are available:
Enhanced User Experience:
We've made it more convenient for our users to access logs and checkpoints by migrating the logs and output folders from Gdrive to Dropbox.
New Models with Improved Performance:
We implemented a modified Fastspeech 2.0. This offers efficiency and pretty high performance. We've made significant steps in enhancing performance on Librispeech, thanks to the implementation of better Conformers and Branchformers. Additionally, we've introduced a performant Conformer Transducer and the SLI-GRU model.
Post-doc Interpretability Techniques:
We now offer improved support for post-doc interpretability techniques. Refer to the ESC50 recipe for more information.
New Datasets:
We've incorporated recipes for new datasets, including the recently released RescueSpeech (speech recognition in rescue and domain environments) and the Zaion Emotion Dataset for Speech Emotion Recognition.
Enhanced Korean ASR:
We've made improvements to KsponSpeech for Korean Automatic Speech Recognition.
Improved Recipe Tests:
We've taken steps to enhance recipe tests, ensuring better reliability and performance.
** Whisper Fixes**:
We've fixed Whisper recipes and interfaces in a way that maintains backward compatibility. This was necessary to address interface changes made in the original model.
Various Fixes:
In addition to the above achievements, we've addressed several other issues, including gradient accumulation and various minor fixes.
Thank you to our dedicated community of contributors and users for making this release possible! We invite you to explore the new features and improvements in SpeechBrain 0.5.15 and look forward to the upcoming release of SpeechBrain 1.0. Happy SpeechBrain-ing!
For a complete list of changes, please refer to the detailed release notes below.
Note truncated.
This release is a minor yet important release. It increases significantly the number of features available while fixing quite a lot of small bugs and
This release is a minor yet important release. It increases significantly the number of features available while fixing quite a lot of small bugs and issues. A summary of the achievements of this release is given below, while a complete detailed list of all the changes can be found at the bottom of this release note.
speechbrain/pretrained/interfaces.py by @jonasvdd in https://github.com/speechbrain/speechbrain/pull/1725avoid_if_longer_than never used by @Adel-Moumen in https://github.com/speechbrain/speechbrain/pull/1882Full Changelog: https://github.com/speechbrain/speechbrain/compare/v0.5.13...v0.5.14
This release is a minor yet important release. It increases significantly the number of features available while fixing quite a lot of small bugs and issues. A summary of the achievements of this release is given below, while a complete detailed list of all the changes can be found at the bottom of this release note.
speechbrain/pretrained/interfaces.py by @jonasvdd in #1725avoid_if_longer_than never used by @Adel-Moumen in #1882Full Changelog: v0.5.13...v0.5.14
This is a minor release with better dependency version specification. We note that SpeechBrain is compatible with PyTorch 1.12, and the updated packag
This is a minor release with better dependency version specification. We note that SpeechBrain is compatible with PyTorch 1.12, and the updated package reflects this. See the issue linked next to each commit for more details about the corresponding changes.
We worked very hard and we are very happy to announce the new version of SpeechBrain!
We worked very hard and we are very happy to announce the new version of SpeechBrain!
SpeechBrain 0.5.12 significantly expands the toolkit without introducing any major interface changes. I would like to warmly thank the many contributors that made this possible.
The main changes are the following:
A) Text-to-Speech: We developed the first TTS system of SpeechBrain. You can find it here. The system relies on Tacotron2 + HiFiGAN (as vocoder). The models coupled with an easy-inference interface are available on HuggingFace.
B) Grapheme-to-Phoneme (G2P): We developed an advanced Grapheme-to-Phoneme. You can find the code here. The current version significantly outperforms our previous model.
C) Speech Separation:
D) Speech Enhancement:
E) Feature Front-ends:
F) Recipe Refactors:
G) Models for African Languages: We now have recipes for the DVoice dataset. We currently support Darija, Swahili, Wolof, Fongbe, and Amharic. The code is available here. The pretrained model (coupled with an easy-inference interface) can be found on SpeechBrain-HuggingFace.
H) Profiler: We implemented a model profiler that helps users while developing new models with SpeechBrain. The profiler outputs a bunch of potentially useful information, such as the real-time factors and many other details. A tutorial is available here.
I) Tests: We significantly improved the tests. In particular, we introduced the following tests: HF_repo tests, docstring checks, yaml-script consistency, recipe tests, and check URLs. This will helps us scale up the project.
L) Other improvements:
Dear users, We worked very hard, and we are very happy to announce the new version of SpeechBrain. SpeechBrain 0.5.11 further expands the toolkit with
Dear users, We worked very hard, and we are very happy to announce the new version of SpeechBrain. SpeechBrain 0.5.11 further expands the toolkit without introducing any major interface change.
The main changes are the following:
Support for Dynamic batching with a Tutorial to help users familiarize themselves with it.
Support for wav2vec training within SpeechBrain.
Developed an interface with Orion for hyperparameter tuning with a Tutorial to help users familiarize themselves with it.
the torchaudio transducer loss is now supported. We also kept our numba implementation to help users customize the transducer loss part if needed.
Improved CTC-Segmentation
Fixed minor bugs and issues (e.g., fixed MVDR beamformer ).
Let me thank all the amazing contributors for this achievement. Please, keep add a star to our project if you appreciate our effort for the community. Together, we are growing very fast, and we have big plans for the future.
Stay Tuned!
This version mainly expands the functionalities of SpeechBrain without adding any backward incompatibilities.
This version mainly expands the functionalities of SpeechBrain without adding any backward incompatibilities.
New Recipes:
Beyond that, we fixed some minor bugs and issues.
This main differences with the previous version are the following:
This main differences with the previous version are the following:
SpeechBrain 0.5.8 improves the previous version in the following way:
SpeechBrain 0.5.8 improves the previous version in the following way:
SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-
SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-of-the-art performance is obtained in various domains. The current version (v0.5.7) supports:
Many other tasks will be supported soon. Take a look into our roadmap on Discourse. Your contribution is welcome! Please, star our project to help us growing.
For more info and tutorials: https://speechbrain.github.io/
Nothing published for this version
Nothing published for this version
Nothing published for this version
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