Verified project record

speechbrain/speechbrain

SpeechBrain is an open-source PyTorch framework designed to accelerate conversational AI development. It provides over 200 training recipes and 100+ pretrained models for building and evaluating speech, text, and EEG processing systems.

Project overview

Project type: Model Runtime · Audio & Speech
Use cases: Meeting Notes · Audio & Speech
Deployment: Refer to project documentation
License: Apache-2.0

Best for

Researchers, AI engineers, and educators who build or customize speech and text processing systems using PyTorch.
Teams requiring over 200 training recipes and 100+ pretrained models for diverse audio, text, and EEG tasks.

Key capabilities

Provides training recipes and technologies for speech recognition, speaker recognition, speech separation, speech enhancement, and sound classification.
Provides training recipes for language modeling, response generation, and grapheme-to-phoneme conversion.
Access over 100 pretrained models hosted on HuggingFace with a user-friendly interface for inference.
The Brain class serves as a fully customizable tool for managing training and evaluation loops over data.
Supports single and multi-GPU training, including distributed training.
Reads large datasets efficiently from a shared Network File System (NFS) via WebDataset.

Limitations and risks

The project is self-hosted only and does not offer a managed service deployment option.
While external services are optional, accessing pretrained models requires HuggingFace, and saving training logs and checkpoints may require Dropbox.
Not suitable for users with no coding skills, as using the framework requires writing Python code.

Getting started

Install the toolkit via pip using a single command, then import it into Python scripts to begin defining training or inference workflows.

Evidence and sources

README: SpeechBrain is an **open-source** [PyTorch](https://pytorch.org/) toolkit that accelerates **Conversational AI** development
README: crafted for fast and easy creation of advanced technologies for **Speech** and **Text** Processing.
README: We share over 200 competitive training [recipes](recipes) on more than 40 datasets supporting 20 speech and text processing tasks (see below).
README: - We support both training from scratch and fine-tuning pretrained models such as [Whisper](https://huggingface.co/openai/whisper-large), [Wav2Vec2](https://huggingface.co/docs/tr…
README: Access over 100 pretrained models hosted on [HuggingFace](https://huggingface.co/speechbrain).

Reviewed at: 2026-07-18T01:58:19Z