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fishaudio/Bert-VITS2

0
View on GitHub↗
8,761 stars·1,292 forks·Python·AGPL-3.0·22 views

Bert VITS2

Bert-VITS2 is a neural speech synthesis system and AI voice generator designed to convert written text into natural sounding audio. It utilizes a VITS2 engine and a neural speech synthesis model to produce high-fidelity human voices.

The system incorporates a multilingual BERT language processor to improve the prosody and emotional accuracy of the generated speech. It supports multilingual voice generation and custom voice cloning to replicate specific human speech patterns and tones.

The architecture covers text-to-speech synthesis through a multi-stage pipeline involving phoneme alignment, stochastic duration prediction, and waveform synthesis. It employs a HiFi-GAN neural vocoder and variational inference to transform text sequences into synthetic audio.

Features

  • Synthetic Speech Generation - Provides high-fidelity synthetic speech generation by converting written text into natural-sounding audio.
  • Neural Vocoders - Ships a HiFi-GAN neural vocoder to convert mel-spectrograms into high-fidelity audio waveforms.
  • Speech Synthesis Models - Implements a neural speech synthesis model for generating high-quality, human-like voices from text.
  • Multilingual Synthesis - Features a multilingual synthesis architecture capable of generating spoken audio in multiple different languages.
  • Multi-Stage Synthesis Pipelines - Employs a multi-stage synthesis pipeline that sequentially processes text through linguistic analysis, duration prediction, and waveform synthesis.
  • Text-to-Speech Synthesis - Converts written text into natural-sounding synthetic speech using neural voice models.
  • Voice Cloning - Supports custom voice cloning to replicate specific human speech patterns and tones.
  • Variational Autoencoders - Implements a variational autoencoder to model latent speech distributions for more natural audio synthesis.
  • Prosodic Duration Predictors - Includes a stochastic duration predictor to ensure natural speech rhythm and avoid robotic timing.
  • Phoneme-Based Speech Processors - Implements a phoneme-based speech processing pipeline that leverages BERT for improved prosody and timing.
  • Semantic Embedding Extractors - Uses a multilingual BERT processor to extract semantic embeddings for improved emotional accuracy and prosody.
  • Synthetic Voice Generators - Functions as an AI voice generator with support for multiple languages and natural intonation.
  • Normalizing Flow Layers - Uses normalizing flow layers to transform simple probability distributions into complex, natural-sounding speech patterns.
  • Text to speech - Listed in the “Text to speech” section of the Ailia Models awesome list.

Star history

Star history chart for fishaudio/bert-vits2Star history chart for fishaudio/bert-vits2

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does fishaudio/bert-vits2 do?

Bert-VITS2 is a neural speech synthesis system and AI voice generator designed to convert written text into natural sounding audio. It utilizes a VITS2 engine and a neural speech synthesis model to produce high-fidelity human voices.

What are the main features of fishaudio/bert-vits2?

The main features of fishaudio/bert-vits2 are: Synthetic Speech Generation, Neural Vocoders, Speech Synthesis Models, Multilingual Synthesis, Multi-Stage Synthesis Pipelines, Text-to-Speech Synthesis, Voice Cloning, Variational Autoencoders.

What are some open-source alternatives to fishaudio/bert-vits2?

Open-source alternatives to fishaudio/bert-vits2 include: kevinwang676/bark-voice-cloning — Bark Voice Cloning is a text-to-speech synthesis engine designed to generate natural-sounding audio and replicate… mozilla/tts — This project is a comprehensive suite for neural speech synthesis, featuring a deep learning text-to-speech engine, a… neonbjb/tortoise-tts — Tortoise-tts is a neural text-to-speech engine and voice cloning toolkit designed for high-quality audio generation.… elevenlabs/elevenlabs-python — This Python SDK provides a comprehensive toolkit for synthetic audio generation, voice cloning, and the development of… snakers4/silero-models — This is a collection of pre-trained neural models for speech recognition, synthesis, and voice activity detection. It… plachtaa/vall-e-x — VALL-E-X is a neural speech synthesis framework and zero-shot text-to-speech engine. It functions as a multilingual…