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.

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

Speech Emotion Recognition on a subset of the RAVDESS dataset.

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

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

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

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

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

Application for Disruptive Situations Detection in public transports through 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.

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.

MFCC features + SVM for speech emotion classification

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

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

😎 Awesome lists about Speech Emotion Recognition