fishaudio/Bert-VITS2
vits2 backbone with multilingual-bert observed · 2026-08-28
Health v2 · maintenance only
63/100
- Activity 99
- Release rhythm 8
- Longevity 80
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: 1131
- days_rel: n/a
- days_push: 9
- n_releases_24m: 0
Adoption not part of the score
8796 stars · 1305 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Bert-VITS2 is a text-to-speech model implementation combining the VITS2 architecture with multilingual BERT embeddings, written in Python. It supports training custom voice models and includes a web UI preprocessing pipeline.
Use cases
- train a custom text-to-speech voice model
- generate speech in multiple languages with bert embeddings
- clone a voice from a dataset
- run a tts webui for inference
- fine-tune vits2 for chinese speech synthesis
When to choose
- you want to train a custom VITS2-based TTS voice with multilingual BERT
- you need an open-source voice cloning pipeline in Python
When to avoid
- you need a state-of-the-art, actively maintained TTS - the authors recommend fish-speech instead
- you need commercial-friendly licensing - it is AGPL-3.0
Facets
library · maturity maintenance
tts machine-learning deep-learning llm-inference speech-processing deep-learning python cross-platform vits2 bert voice-cloning speech-synthesis vocoder text-to-speech natural-language-processing
1 source
- readme: https://github.com/fishaudio/Bert-VITS2 · fetched 2026-08-28 · dd74c654e269
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| fishaudio/Bert-VITS2 | main | 63 |
For agents
markdown · JSON · MCP: product_card(name="fishaudio/Bert-VITS2")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem