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speechbrain

speechbrain/speechbrain

A PyTorch-based Speech Toolkit

GraphCanon updated 3w · GitHub synced 3w

12k stars1.7k forksLast push 2mo Python Apache-2.0

Decision brief

SpeechBrain provides comprehensive speech processing capabilities built on PyTorch, ideal for tasks like automatic speech recognition and audio enhancement. It is open-source under the Apache-2.0 license.

Good fit when

  • If you need to customize or experiment extensively with your speech processing pipeline, as SpeechBrain allows easy modifications via editable installs.
  • For researchers and developers aiming to work on a wide range of tasks including ASR, speaker verification, and audio enhancement within the same toolkit.

Avoid when

  • If simplicity and ease of use are top priorities. SpeechBrain's extensive features might introduce unnecessary complexity for simpler speech processing tasks.
  • Avoid if you are constrained by computational resources, as expanding efforts toward training massive models could be resource-intensive and is one of the toolkit’s future development goals.

Observed Jul 17, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Steady (44d since push)
As of 3w
Provenance
Not a fork · Organization account
As of 3w
Security (OSV)
93 low (93 low)
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install speechbrain
PyPI

How it fits your stack(1)

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Relationship graph

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Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

SpeechBrain is a toolkit designed for research and development in speech processing tasks such as automatic speech recognition (ASR), speaker verification, audio enhancement, diarization, and more.

Capability facts

Languages
python

Source: github.language+pyproject.toml · Jul 30, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 30, 2026)

2. Access SpeechBrain in your Python code:
Source link

Tags

README

🚀 Quick Start

To get started with SpeechBrain, follow these simple steps:


Install via PyPI

  1. Install SpeechBrain using PyPI:

    pip install speechbrain
    
  2. Access SpeechBrain in your Python code:

    import speechbrain as sb
    

Install from GitHub

This installation is recommended for users who wish to conduct experiments and customize the toolkit according to their needs.

  1. Clone the GitHub repository and install the requirements:

    git clone https://github.com/speechbrain/speechbrain.git
    cd speechbrain
    pip install -r requirements.txt
    pip install --editable .
    
  2. Access SpeechBrain in your Python code:

    import speechbrain as sb
    

Any modifications made to the speechbrain package will be automatically reflected, thanks to the --editable flag.


✔️ Test Installation

Ensure your installation is correct by running the following commands:

pytest tests
pytest --doctest-modules speechbrain

📜 License

  • SpeechBrain is released under the Apache License, version 2.0, a popular BSD-like license.
  • You are free to redistribute SpeechBrain for both free and commercial purposes, with the condition of retaining license headers. Unlike the GPL, the Apache License is not viral, meaning you are not obligated to release modifications to the source code.

🔮Future Plans

We have ambitious plans for the future, with a focus on the following priorities:

  • Scale Up: We aim to provide comprehensive recipes and technologies for training massive models on extensive datasets.

  • Scale Down: While scaling up delivers unprecedented performance, we recognize the challenges of deploying large models in production scenarios. We are focusing on real-time, streamable, and small-footprint Conversational AI.

  • Multimodal Large Language Models: We envision a future where a single foundation model can handle a wide range of text, speech, and audio tasks. Our core team is focused on enabling the training of advanced multimodal LLMs.

For agents

This page has a .md twin and JSON over the API.

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