Bert-VITS2-ext

Introduction

Bert-VITS2-ext is an extension of the Bert-VITS2 model designed for animation testing, focusing on generating facial expressions and body animations from audio inputs. This project aims to enhance the capabilities of text-to-speech (TTS) systems by synchronizing audio with visual expressions and movements.

Key Features

• Facial Expression Generation: Converts audio input into corresponding facial expressions using advanced encoding techniques.
• Body Animation: Generates body movements that match the audio content, allowing for more immersive interactions.
• Integration with MotionGPT: Utilizes MotionGPT for generating motion descriptions based on audio and expressions.
• Data Collection and Preprocessing: Provides tools for collecting and preprocessing data to train the model effectively.
• Open Source: Available on GitHub, allowing developers to contribute and enhance the project.

Benefits

• Enhanced User Experience: By synchronizing audio with visual elements, it creates a more engaging experience for users.
• Versatile Applications: Suitable for various applications, including gaming, virtual reality, and animated content creation.
• Community Support: Being an open-source project, it benefits from community contributions and improvements.