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jik876/hifi-gan

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis observed · 2026-08-28

github.com/jik876/hifi-gan · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2149
  • days_rel: n/a
  • days_push: 767
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

2367 stars · 557 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The official PyTorch implementation of HiFi-GAN, a generative adversarial network that converts mel-spectrograms into high-fidelity 22.05 kHz audio faster than real time on a single GPU. It ships with training scripts, multiple generator configurations, and pretrained checkpoints for LJSpeech and VCTK, including versions fine-tuned for Tacotron2 and universal multi-speaker use.

Use cases

  • convert mel-spectrograms to audio waveforms
  • add a vocoder to a text-to-speech pipeline
  • generate high fidelity speech from spectrograms
  • train a GAN vocoder on my own dataset
  • download a pretrained vocoder model
  • run real-time speech synthesis on GPU or CPU
  • fine-tune a vocoder for Tacotron2 output

When to choose

  • You need a proven, high-quality vocoder with ready-to-use pretrained checkpoints (LJSpeech, VCTK, Tacotron2 fine-tuned)
  • You want faster-than-real-time waveform generation, including a small-footprint model that runs 13x faster than real time on CPU
  • You are reproducing the HiFi-GAN paper or building research on top of it
  • You work in Python/PyTorch and want reference training and inference code

When to avoid

  • You need a complete end-to-end TTS system - this is a vocoder only, with no text normalization, phonemization, or acoustic model included
  • You need ONNX, TensorFlow, or non-Python deployment support - the official code is PyTorch-only
  • You require guaranteed ongoing maintenance or new features - the repo is a research artifact updated sporadically
  • You need production streaming or low-latency chunked inference support out of the box

Facets

library · maturity stable

tts audio-processing machine-learning deep-learning speech-processing deep-learning machine-learning artificial-intelligence python cli cross-platform vocoder gan speech-synthesis mel-spectrogram-inversion pytorch pretrained-models text-to-speech research-implementation audio gpu

1 source

Member repositories

RepositoryRoleHealth v2
jik876/hifi-ganmain32

For agents

markdown · JSON · MCP: product_card(name="jik876/hifi-gan")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem