Video
ai-avatar-system
Talking AI avatars — upload a photo, clone a voice, lip-sync in real time.
★ 516 SterneMIT
Anleitung ansehen →TalkMateAI ist ein Open-Source-Projekt aus der Kategorie Video von kiranbaby14 (kiranbaby14/TalkMateAI auf GitHub). Es hat 111 Sterne auf GitHub und 24 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 23. Mai 2026 auf GitHub aktualisiert.
A real-time voice-driven 3D avatar with multimodal AI.
Get the full-stack source.
Install the FastAPI services.
Install the Next.js app.
Speak and watch it respond.
Speak naturally to the avatar.
An animated companion character.
Vision-language understanding.
Natural voice synthesis.
FastAPI plus Next.js.
Free and open source.
Download the source and enter the folder.
git clone https://github.com/kiranbaby14/TalkMateAI.git
cd TalkMateAIInstall the Python services.
pip install -r requirements.txtInstall and run the Next.js app.
cd web && npm install && npm run devA real-time voice-controlled 3D avatar with multimodal AI, at kiranbaby14/TalkMateAI.
By voice; it listens and responds as a 3D character.
FastAPI backend, Next.js frontend, Kokoro TTS, SmolVLM.
Yes. MIT licensed.
Yes. Designed for live voice interaction.
Talking AI avatars — upload a photo, clone a voice, lip-sync in real time.
🚀 Truly open-source AI avatar(digital human) toolkit for offline video generation and digital human cloning
Live2D and VRM voice avatar with lip sync you can embed anywhere.
Research code for real-time interactive video via diffusion distillation.
Real-time long video generation — a research model built for speed.
3D talking avatar linked to Claude Code CLI - voice conversation with lip-sync
Die anderen Projekte der Kategorie Video mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls TalkMateAI nicht das Richtige ist.
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Verwandte Projekte der Kategorie Video im Katalog, die TalkMateAI bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
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YouTube summaries and timestamps via Gemini or GPT.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.