3 dépôts
Analysis of user affective states through physiological or behavioral markers to adapt software behavior.
Distinct from User Behavior Analysis: Focuses on immediate emotional state detection (affective computing) rather than long-term user behavior patterns.
Explore 3 awesome GitHub repositories matching data & databases · Emotion Analysis. Refine with filters or upvote what's useful.
HomeMirror is an Android application designed to turn a tablet or screen into a smart mirror and personal information dashboard. It provides a specialized user interface for wall-mounted displays that integrates external data providers with personal scheduling. The system includes a vision-based facial expression analysis tool that detects a user's mood through camera input to adjust the visual display of the information dashboard. The application aggregates real-time data including weather, calendar events, and financial stock price fluctuations. It also tracks personal reminders such as da
Detects facial expressions to identify the user's emotional state and adjust the visual display.
clmtrackr is a JavaScript computer vision library designed for facial landmark detection and real-time tracking. It implements Constrained Local Models to identify specific coordinate points on a human face within video feeds or static images. The project functions as a real-time face warping engine and expression analysis tool. It can distort facial images via parametric models to create caricatures or identify and label emotional states such as happiness, sadness, anger, and surprise based on feature coordinates. The library covers a broad range of capabilities including automatic and manu
Analyzes facial feature coordinates to identify and label emotional states such as happiness, sadness, anger, and surprise.
This project is an Android SDK designed to integrate conversational voice interfaces into mobile applications. It utilizes a Model-View-ViewModel architecture to separate business logic from user interface components, providing a structured framework for managing complex voice interactions. The library features a modular pipeline that handles the entire flow of a conversation, including microphone input capture, speech transcription, intelligent response generation, and audio synthesis. A key differentiator is its ability to analyze acoustic features from audio input to detect user emotional
Analyzes acoustic features to identify emotional states and injects this context into prompts for adaptive responses.