# neonbjb/tortoise-tts

A multi-voice TTS system trained with an emphasis on quality

Repository: https://github.com/neonbjb/tortoise-tts
Canonical: https://ross.abutalabs.com/products/tortoise-tts
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Last push: 2024-11-19T18:59:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1678, "days_push": 652, "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 14870, forks 2037 (observed 2026-08-28T04:11:08.844701+00:00)

## What it is
Tortoise TTS is a multi-voice text-to-speech library built on PyTorch that prioritizes highly realistic prosody and intonation. It combines an autoregressive decoder and a diffusion decoder for high-quality speech generation, installable via pip.

## Use cases
- generate realistic speech from text
- create multi-voice audio narrations
- synthesize speech with natural prosody and intonation
- clone or use multiple voices for TTS
- add high-quality voice output to Python applications

## When to choose
- you need top-quality, realistic speech rather than fastest generation
- you want multi-voice support and expressive prosody
- you have an NVIDIA GPU and a Python/PyTorch workflow

## When to avoid
- you need real-time or low-latency TTS on modest hardware
- you lack an NVIDIA GPU
- you need lightweight, on-device or embedded speech synthesis

## Facets
- artifact type: library
- maturity: maintenance
- function: tts, machine-learning, deep-learning
- domain: speech-processing, artificial-intelligence
- platform: python, cross-platform
- tags: text-to-speech, multi-voice, diffusion, voice-cloning, pytorch, audio, gpu

## Member repositories
- neonbjb/tortoise-tts (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:08.844701+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 2026-08-29T17:07:01.312435+00:00, confidence not recorded.
  - readme: https://github.com/neonbjb/tortoise-tts (fetched 2026-08-28T04:11:08.844701+00:00, sha 07dcac086d42)
  - registry_pypi: https://pypi.org/pypi/tortoise-tts/json (fetched 2026-08-29T08:05:00.813029+00:00, sha 2c63993178e6)
- Data as of 2026-08-30T08:39:29.467469+00:00.