GraphCanon
Home/Model Training/espnet
espnet logo

espnet

Enrichment pending
espnet/espnet

End-to-End Speech Processing Toolkit

GitHub Website

GraphCanon updated today · GitHub synced today

9.9k
Stars
2.4k
Forks
65
Open issues
169
Watchers
1d
Last push
Python Apache-2.0Created Dec 13, 2017

Trust & integrity

Full report
Maintenance
Very active (0d since push)
As of today · Source: github_public_v1
Provenance
Not a fork · Organization account
As of today · Source: github_public_v1
Security (OSV)
No lockfile
As of today · Source: none

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

Overview

End-to-End Speech Processing Toolkit

Capability facts

Languages
python

Source: github.language+pyproject.toml · Jul 11, 2026

Categories

Model TrainingSpeech & AudioDeveloper Tools

Compatibility

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

Python runtimePython

Source: README excerpt (regex_v1, Jul 11, 2026)

- If you just need the Python module only:
Source link

Tags

speaker-diarizationdeep-learningkaldichainerend-to-endmachine-translationpytorchsinging-voice-synthesis

README

Installation

  • If you intend to do full experiments, including DNN training, then see Installation.

  • If you just need the Python module only:

    # We recommend you install PyTorch before installing espnet following https://pytorch.org/get-started/locally/
pip install espnet
# To install the latest
# pip install git+https://github.com/espnet/espnet
# To install additional packages
# pip install "espnet[all]"

    If you use ESPnet1, please install chainer and cupy.

    pip install chainer==6.0.0 cupy==6.0.0    # [Option]

    You might need to install some packages depending on each task. We prepared various installation scripts at tools/installers.

  • (ESPnet2) Once installed, run wandb login and set --use_wandb true to enable tracking runs using W&B.

Docker Container

go to docker/ and follow instructions.