Example projects built with the Hume AI APIs

Files relevant for my bachelor thesis on different automatic emotion recognition approaches

Foundational Model for Speech Recognition Tasks

Reward Penalty Weighted Ensemble approach for multimodal data stream classification

The project develops a facial emotion classifier using the k-Nearest Neighbors (kNN) algorithm. The classifier uses Histogram of Oriented Gradients (HOG) and Principal Component Analysis (PCA) for dimensionality reduction with usage of normalisaton, preprocessing and augmentation.

GraphCNN + CNN Network for EEG Emotion Recognition

GCNN for EEG Emotion Recognition

Classification of Emotions based on EEG Signals (SEED Dataset)

Official code repository for paper "Multi-modal Speech Emotion Recognition using Multi-head Attention Fusion of Multi-feature Embeddings". Paper accepted to EAI INISCOM 2023

Multimodal Emotion Recognition System

Extracting emotion from sound by looking at sound file's features and the meaning of the sentences using NLTK and LSTM.

The AI-powered ser Python package is a tool for recognizing and analyzing emotions in speech. Employing state-of-the-art machine learning and audio processing techniques, it classifies emotions in audio recordings, extracts transcripts, and integrates these with a timeline of emotional states

Identifying and categorizing opinions , emotions, and attitudes of movie reviews within textual data.

😎 Awesome lists about Speech Emotion Recognition

The detection of emotion is made by using the machine learning concept. You can use the trained dataset to detect the emotion of the human being. For detecting the different emotions, first, you need to train those different emotions, or you can use a dataset already available on the internet.

ABAW6 (CVPR-W) We achieved second place in the valence arousal challenge of ABAW6

Multimodal Emotion eXpression Capture Amsterdam. Pipeline for capturing emotion expressions from multiple modalities (video, audio, text) in the wild.

This project implements a real-time face emotion recognition system using Gray-Level Co-Occurrence Matrix (GLCM) for feature extraction and an Artificial Neural Network (ANN) for classification. The system can identify various emotional states from facial expressions in real-time.

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

基于transformer实现的表情包推荐系统