lipku/LiveTalking

What it solves

LiveTalking is a real-time interactive streaming engine for digital humans. It solves the challenge of creating lifelike, synchronized audio-visual dialogue interfaces where a virtual avatar can speak in real-time based on text or voice input, enabling applications like AI customer service, virtual livestreaming, and automated educational content.

How it works

The system follows a pipeline: user input (text/audio) $\rightarrow$ LLM for response generation $\rightarrow$ TTS for voice synthesis $\rightarrow$ digital human lip-syncing $\rightarrow$ streaming output. It uses deep learning models such as Wav2Lip, MuseTalk, and ER-NeRF to generate lip movements that match the audio features (like Mel spectrograms) and blends these movements back into high-definition video.

Who it’s for

• Content Creators: For 24/7 unmanned livestreaming and bulk short-video production.
• Businesses: For AI-driven customer service and interactive exhibition displays.
• Educators: For creating digital teacher clones for real-time or recorded instruction.
• Developers: Those needing an API-driven framework to integrate digital humans into apps or smart speakers.

Highlights

• Multi-Model Support: Compatible with ernerf, musetalk, wav2lip, and Ultralight-Digital-Human.
• Flexible Output: Supports WebRTC for low-latency browser streaming, RTMP for platforms like YouTube/Bilibili, and virtual camera output.
• Interactive Features: Supports voice cloning, the ability to be interrupted while speaking, and custom action orchestration (playing specific videos when silent).
• Extensible Architecture: Features a decentralized registry system for adding custom TTS, Avatar, and Output modules.