🎭 Deep Learning project for video-based emotion recognition using CNN, LSTM & Autoencoder. Combines spatial feature extraction, temporal modeling & unsupervised learning for accurate classification of human emotions from video sequences. Built with TensorFlow/Keras.

A project to classify emotions like happiness, sadness, and anger from speech using MFCCs, machine learning models, and visualizations for audio features and model performance.

Emotion and Voice Detection using Machine Learning Python Project. This Project about to detect human Voice and Facial emotion

Emotion Recognition from Audio (ERA) is an innovative project that classifies human emotions from speech using advanced machine learning techniques.

Implementing a Speech Emotion Recognition (SER) system using deep learning. It extracts audio features from the CREMA-D dataset and trains both 1D and 2D Convolutional Neural Networks (CNNs) to classify emotions from speech.

👩🏿‍💻IIIT Hyderabad Reasearch Teaser Programme : We developed a robust emotion😃 recognition system utilizing machine learning techniques on the 🗣️CREMA-D dataset to classify various emotions expressed in audio recordings🎙️ accurately.

A machine learning project that aims to classify various emotional states of a human based on audio recordings using the CREMA-D dataset

An attempt at the speech emotion recognition (SER) task on the CREMA-D dataset using TensorFlow 1D & 2D RCNN models.