An implementation of Speech Emotion Recognition, based on HuBERT model, training with PyTorch and HuggingFace framework, and fine-tuning on the RAVDESS dataset.

MFCC features + SVM for speech emotion classification

😎 Awesome lists about Speech Emotion Recognition

Exploration of different audio features and CNN-based architectures for building an effective Speech Emotion Recognition (SER) system. The goal is to improve the accuracy of detecting emotions embedded in speech signals. The repository contains code, notebook, and detailed explanations of the experiments conducted.

Transformer-based model for Speech Emotion Recognition(SER) - implemented by Pytorch

Repository for PhD activity (dissertation S3) with focus on speech emotion recognition, JAIST 2017~2021

Domain-shift Aware Meta-Learning for Domain Generalization in SER

Application for Disruptive Situations Detection in public transports through Speech Emotion Recognition.

Classify emotions like happy, fear, neutral, etc. using CNN applying bootstrap aggregation approach

In this work is proposed a speech emotion recognition model based on the extraction of four different features got from RAVDESS sound files and stacking the resulting matrices in a one-dimensional array by taking the mean values along the time axis. Then this array is fed into a 1-D CNN model as input.

Speech Emotion Recognition on a subset of the RAVDESS dataset.

A Convolutional Neural Network that distinguishes between the speakers emotions. Comes with multiple preprocessors to improve the models performance.

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

This repository contains the source code for my final year project for my undergraduate degree in MTU.

Hybrid Data Augmentation and Attention-based Dilated Convolutional-Recurrent Neural Networks for Speech Emotion Recognition

Speech Emotion Recognition (SER) using Deep neural networks CNN and RNN