About this document

Speech Emotion Recognition Overview by Arash Mari Oriyad is a document available to read on EtoBox.

This document discusses speech emotion recognition (SER). It provides an overview of SER, including defining the problem, gathering data, selecting features, and designing models. Popular datasets for SER are described, such as RAVDESS and EMO-DB. Common feature extraction methods like LPCC, MFCC, and TEO are explained. Classification models like HMM, GMM, DNN are covered. Results show MFCC features achieving the highest accuracy of 82.3% using HMM models. The document provides context and details about SER

Author

Arash Mari Oriyad

Language

EN