Home/Speech & Audio/ParallelWaveGAN
ParallelWaveGAN logo

ParallelWaveGAN

kan-bayashi/ParallelWaveGAN

Unofficial Parallel WaveGAN (+ variants) with Pytorch for speech synthesis

GraphCanon updated today · GitHub synced today

1.6k
Stars
352
Forks
43
Open issues
45
Watchers
2y
Last push
Jupyter Notebook MITCreated Oct 29, 2019

Trust & integrity

Full report
Maintenance
Dormant (810d since push)
As of today · Source: github_public_v1
Provenance
Not a fork · Personal 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

Repository containing implementations of various neural vocoders such as MelGAN, Multi-band MelGAN, HiFi-GAN, and StyleMelGAN using PyTorch.

Capability facts

Languages
jupyter notebook

Source: github.language · Jul 11, 2026

Categories

Compatibility

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

Python runtimePython

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

- Python 3.8+
Source link

Tags

README

Requirements

This repository is tested on Ubuntu 20.04 with a GPU Titan V.

  • Python 3.8+
  • Cuda 11.0+
  • CuDNN 8+
  • NCCL 2+ (for distributed multi-gpu training)
  • libsndfile (you can install via sudo apt install libsndfile-dev in ubuntu)
  • jq (you can install via sudo apt install jq in ubuntu)
  • sox (you can install via sudo apt install sox in ubuntu)

Different cuda version should be working but not explicitly tested.
All of the codes are tested on Pytorch 1.8.1, 1.9, 1.10.2, 1.11.0, 1.12.1, 1.13.1, 2.0.1 and 2.1.0.


If you want to use distributed training, please install


command to install apex.

$ make apex


Note that we specify cuda version used to compile pytorch wheel.  
If you want to use different cuda version, please check `tools/Makefile` to change the pytorch wheel to be installed.

---

# If not, please install via pip
$ pip install parallel_wavegan

---

# Please install this repository in ESPnet conda (or virtualenv) environment
$ . ./path.sh && pip install -U parallel_wavegan