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

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.

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.

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

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

🎭 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.

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