A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
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Updated
Jun 6, 2024 - Python
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
Files relevant for my bachelor thesis on different automatic emotion recognition approaches
EmoTunes, an incredible music app that allows you to discover and enjoy songs based on your current facial emotions.
😎 Awesome lists about Speech Emotion Recognition
Large-Scale Selfie Video Dataset (L-SVD): A Benchmark for Emotion Recognition
This repository houses a robust speech emotion recognition system, featuring signal processing scripts, machine learning algorithms, and comprehensive documentation. It accurately classifies emotions in spoken language, enabling applications like sentiment analysis and emotion-aware systems.
Example projects built with the Hume AI APIs
Facial Emotion Recognition using OpenCV and Deepface
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
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.
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.
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