# SparkAudio/Spark-TTS

Spark-TTS Inference Code

Repository: https://github.com/SparkAudio/Spark-TTS
Canonical: https://ross.abutalabs.com/products/spark-tts
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2025-04-09T10:18:00+00:00

## Health v2 (maintenance only)
Score: 27/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 15, release rhythm 35, longevity 39
- inputs: {"age_days": 555, "days_push": 511, "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 11006, forks 1156 (observed 2026-08-28T04:10:45.840790+00:00)

## What it is
Spark-TTS is an LLM-based text-to-speech system built on Qwen2.5 that generates speech directly from single-stream decoupled speech tokens. This repository provides the official PyTorch inference code and pretrained 0.5B model supporting zero-shot voice cloning and bilingual (Chinese/English) synthesis.

## Use cases
- clone a voice from a short audio sample without training
- convert text to natural-sounding speech in Chinese and English
- run zero-shot cross-lingual voice synthesis
- generate speech with controllable parameters like speed and pitch
- integrate LLM-based TTS into a production pipeline
- experiment with decoupled speech token models for research

## When to choose
- you need zero-shot voice cloning without per-speaker training
- you want efficient TTS without extra flow-matching or acoustic models
- you need bilingual Chinese-English or code-switching synthesis
- you want an Apache-2.0 licensed TTS with a small 0.5B model

## When to avoid
- you need many languages beyond Chinese and English
- you require a fully managed cloud TTS API rather than self-hosted inference
- you need real-time streaming synthesis with guaranteed low latency
- you lack a GPU and need fast inference on CPU only

## Facets
- artifact type: library
- maturity: active
- function: tts, llm-inference, speech-recognition, machine-learning
- domain: speech-processing, artificial-intelligence, large-language-models
- platform: python
- tags: voice-cloning, zero-shot-tts, bilingual, qwen2, pytorch, text-to-speech, linux, gpu

## Member repositories
- SparkAudio/Spark-TTS (main) score 27

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:45.840790+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 2026-08-29T17:17:13.967709+00:00, confidence not recorded.
  - readme: https://github.com/SparkAudio/Spark-TTS (fetched 2026-08-28T04:10:45.840790+00:00, sha d9abab62332b)
- Data as of 2026-08-30T08:39:29.467469+00:00.