awakening-ai

awakening-ai / ReactMotion

Public

ReactMotion: Generating Reactive Listener Motions from Speaker Utterance

14
0
100% credibility
Found Mar 18, 2026 at 14 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

ReactMotion is an AI system that generates natural body motions for a listener reacting to a speaker's text, audio, and emotions, with demos, pretrained models, and full training code.

How It Works

1
👀 Discover ReactMotion

You stumble upon this fun project that creates realistic body movements for someone listening and reacting to a speaker's words.

2
📱 Watch the demo video

See example videos where listeners nod, smile, or gesture naturally in response to excited or sad speech.

3
🖥️ Launch the web playground

Click to open a simple online tool where you type words, upload voice clips, or pick feelings like happy or surprised.

4
✨ Generate reactions

Watch as it instantly creates several lifelike motion videos of a listener responding just right.

5
⚙️ Tweak and create more

Adjust settings like creativity level to get diverse, perfect reactions for your scene.

🎉 Your custom animations ready

Download the videos to bring conversations to life in your videos, stories, or apps.

Sign up to see the full architecture

4 more

Sign Up Free

Star Growth

See how this repo grew from 14 to 14 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is ReactMotion?

ReactMotion, a Python project on react motion github, generates reactive listener motions from speaker utterances by processing text transcriptions, raw audio, or emotion labels. It produces diverse 3D body animations—like nods, gestures, or leans—that naturally respond to what the speaker says, tackling the one-to-many nature of real human reactions in conversations. Users get quick video outputs via CLI demos or a Gradio web UI, with pretrained models on Hugging Face.

Why is it gaining traction?

It introduces a fresh task: modeling listener responses beyond static text-to-motion, with flexible conditioning from text-only to full text+audio+emotion. The preference-ranked training ensures varied, appropriate outputs, plus a scorer for picking the best from multiples. Devs dig the end-to-end pipeline—install, download models, run inference or train on your data.

Who should use this?

AI researchers in motion generation testing multimodal dialogue systems, devs building virtual agents or avatars that react to speech in video calls, or anyone prototyping embodied AI for conversations needing realistic nonverbal feedback.

Verdict

Worth forking for reactmotion experiments (1.0% credibility, 14 stars signals early days), with strong docs, HF models, and Gradio ready out-of-box. Maturity lags on tests/community, but solid for research prototypes—demo it before committing.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.