# r9y9/wavenet_vocoder

WaveNet vocoder

Repository: https://github.com/r9y9/wavenet_vocoder
Canonical: https://ross.abutalabs.com/products/wavenet_vocoder
Homepage: https://r9y9.github.io/wavenet_vocoder/
Language: Python
License: NOASSERTION
License Family: other
Topics: wavenet, speech-synthesis, speech-processing, pytorch, python, wavenet-vocoder, neural-vocoder, speech
Last push: 2023-07-29T04:47:53+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3171, "days_push": 1131, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2376, forks 493 (observed 2026-08-28T04:06:42.067967+00:00)

## What it is
A PyTorch implementation of the WaveNet vocoder that generates high-quality raw speech waveforms conditioned on acoustic features like mel-spectrograms. It includes pre-trained models and fast inference via cached convolution states, and integrates with ESPnet for full text-to-speech pipelines.

## Use cases
- generate raw audio waveforms from mel-spectrograms
- build a text-to-speech pipeline with Tacotron2 and a neural vocoder
- train a WaveNet vocoder on a custom speech dataset
- synthesize speech with speaker embeddings for multi-speaker TTS
- experiment with mixture of logistics audio modeling
- speed up vocoder inference with cached convolutions

## When to choose
- you need a neural vocoder to convert mel-spectrograms into audio
- you want a PyTorch WaveNet implementation with pre-trained LJSpeech models
- you are integrating a vocoder into an ESPnet-based TTS system

## When to avoid
- you need a full text-to-speech model that converts raw text directly to speech
- you need fast real-time vocoding on CPU
- you want an actively developed project with recent updates and support

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, audio-processing, speech-recognition
- domain: speech-processing, machine-learning, deep-learning
- platform: python, cross-platform
- tags: wavenet, vocoder, text-to-speech, pytorch, mel-spectrogram, pretrained-models, speech-synthesis, audio

## Member repositories
- r9y9/wavenet_vocoder (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:42.067967+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:35:00.205284+00:00, confidence not recorded.
  - readme: https://github.com/r9y9/wavenet_vocoder (fetched 2026-08-28T04:06:42.067967+00:00, sha 7692bdc8a432)
  - homepage: https://r9y9.github.io/wavenet_vocoder/ (fetched 2026-08-29T10:15:55.693160+00:00, sha 46350808e86e)
- Data as of 2026-08-30T08:39:29.467469+00:00.