# spring-media/TransformerTTS

🤖💬 Transformer TTS: Implementation of a non-autoregressive Transformer based neural network for text to speech.

Repository: https://github.com/spring-media/TransformerTTS
Canonical: https://ross.abutalabs.com/products/transformertts
Homepage: https://as-ideas.github.io/TransformerTTS/
Language: Python
License: NOASSERTION
License Family: other
Topics: deep-learning, axelspringerai, text-to-speech, python, tensorflow, tts
Archived: true
Last push: 2024-05-03T19:50:55+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2351, "days_push": 852, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1161, forks 223 (observed 2026-08-28T04:03:49.417642+00:00)

## What it is
A TensorFlow 2 implementation of a non-autoregressive Transformer-based neural network for text-to-speech synthesis, based on FastSpeech and FastPitch papers. It includes pre-trained LJSpeech models compatible with vocoders like MelGAN and HiFiGAN, with controllable speed and pitch.

## Use cases
- synthesize speech from text with a transformer model
- generate fast non-autoregressive TTS audio
- control speed and pitch of generated speech
- train a FastSpeech-style TTS model on custom datasets
- convert text to mel spectrograms for vocoders like MelGAN or HiFiGAN
- run text-to-speech inference from the command line or Colab

## When to choose
- you need a TensorFlow-based non-autoregressive TTS implementation
- you want fast, robust speech synthesis without autoregressive failure modes
- you need controllable pitch and speed in synthesized speech
- you want to train or fine-tune a FastSpeech/FastPitch-style model

## When to avoid
- you need a production-ready TTS service with active development
- you prefer PyTorch-based TTS tooling
- you need the latest state-of-the-art TTS quality
- you require Windows support out of the box

## Facets
- artifact type: library
- maturity: maintenance
- function: tts, machine-learning, deep-learning
- domain: speech-processing, deep-learning
- platform: python
- tags: text-to-speech, tensorflow, transformer, non-autoregressive, fastspeech, ljspeech, speech-synthesis, vocoder, natural-language-processing, linux, macos

## Member repositories
- spring-media/TransformerTTS (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:49.417642+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 2026-08-30T06:31:44.660833+00:00, confidence not recorded.
  - readme: https://github.com/spring-media/TransformerTTS (fetched 2026-08-28T04:03:49.417642+00:00, sha 04b9a5d1080b)
- Data as of 2026-08-30T08:39:29.467469+00:00.