# ibab/tensorflow-wavenet

A TensorFlow implementation of DeepMind's WaveNet paper

Repository: https://github.com/ibab/tensorflow-wavenet
Canonical: https://ross.abutalabs.com/products/tensorflow-wavenet
Language: Python
License: MIT
License Family: permissive
Last push: 2023-07-12T06:15:53+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3642, "days_push": 1148, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5428, forks 1265 (observed 2026-08-28T04:09:17.983311+00:00)

## What it is
A TensorFlow implementation of DeepMind's WaveNet generative neural network architecture for raw audio waveform generation. It provides training and generation scripts that model the conditional probability of the next audio sample using causal dilated convolutions.

## Use cases
- generate raw audio waveforms with a neural network
- train a WaveNet model on a corpus of wav files
- implement DeepMind's WaveNet paper in TensorFlow
- build a neural vocoder for audio synthesis
- experiment with causal dilated convolutions for audio
- text-to-speech audio generation research

## When to choose
- you want an open-source reference implementation of WaveNet for research or learning
- you need to train an audio generation model on your own wav corpus
- you are studying generative models of raw audio in TensorFlow

## When to avoid
- you need a production-ready, actively maintained TTS engine
- you want fast, real-time audio synthesis without GPUs
- you need support for recent TensorFlow 2.x versions out of the box
- you want a simple high-level API rather than training scripts

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, audio-processing, machine-learning, tts
- domain: deep-learning, machine-learning, speech-processing
- platform: python, cross-platform
- tags: wavenet, tensorflow, generative-model, audio-generation, neural-vocoder, research-code, audio, gpu, linux, macos

## Member repositories
- ibab/tensorflow-wavenet (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:17.983311+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 2026-08-29T17:56:54.841769+00:00, confidence not recorded.
  - readme: https://github.com/ibab/tensorflow-wavenet (fetched 2026-08-28T04:09:17.983311+00:00, sha 0a85ce5bd492)
- Data as of 2026-08-30T08:39:29.467469+00:00.