# ming024/FastSpeech2

An implementation of Microsoft's "FastSpeech 2: Fast and High-Quality End-to-End Text to Speech"

Repository: https://github.com/ming024/FastSpeech2
Canonical: https://ross.abutalabs.com/products/fastspeech2
Language: Python
License: MIT
License Family: permissive
Last push: 2023-10-27T04:35:58+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": 2260, "days_push": 1041, "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 2185, forks 616 (observed 2026-08-28T04:06:23.642297+00:00)

## What it is
A PyTorch implementation of Microsoft's FastSpeech 2 text-to-speech model, supporting English and Mandarin with single- and multi-speaker synthesis. It includes pretrained checkpoints, MelGAN/HiFi-GAN vocoder support, and controllable pitch, volume, and speaking rate.

## Use cases
- synthesize speech from text in Python
- train a FastSpeech 2 TTS model on LJSpeech
- build a multi-speaker English or Mandarin TTS system
- control pitch and speaking rate of generated speech
- generate audio samples with HiFi-GAN vocoder
- reproduce FastSpeech 2 research results

## When to choose
- you need a FastSpeech 2 implementation with pretrained checkpoints
- you want controllable TTS with pitch/volume/rate adjustment
- you need multi-speaker TTS for English or Mandarin
- you want a PyTorch codebase to extend for TTS research

## When to avoid
- you need the latest state-of-the-art TTS models like VITS or diffusion-based systems
- you want a production-ready TTS service with an API
- you need languages other than English or Mandarin
- you prefer a maintained library with active development

## Facets
- artifact type: library
- maturity: maintenance
- function: tts, machine-learning, deep-learning
- domain: speech-processing, deep-learning
- platform: python, cross-platform
- tags: text-to-speech, pytorch, fastspeech2, vocoder, melgan, hifi-gan, multi-speaker, natural-language-processing

## Member repositories
- ming024/FastSpeech2 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:23.642297+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 2026-08-30T02:48:11.992673+00:00, confidence not recorded.
  - readme: https://github.com/ming024/FastSpeech2 (fetched 2026-08-28T04:06:23.642297+00:00, sha 3b8ff0f46c24)
- Data as of 2026-08-30T08:39:29.467469+00:00.