Multilingual vocal emotion recognition and classification using back propagation neural network

This work implements classification of different emotions in different languages using Artificial Neural Networks (ANN). Mel Frequency Cepstral Coefficients (MFCC) and Short Term Energy (STE) have been considered for creation of feature set. An emotional speech corpus consisting of 30 acted utteranc...

Full description

Saved in:
Bibliographic Details
Main Authors: Kayal, Apoorva J., Nirmal, Jagannath
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Back propagation networks
Classification
Emotion recognition
Emotions
Languages
Neural networks
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This work implements classification of different emotions in different languages using Artificial Neural Networks (ANN). Mel Frequency Cepstral Coefficients (MFCC) and Short Term Energy (STE) have been considered for creation of feature set. An emotional speech corpus consisting of 30 acted utterances per emotion has been developed. The emotions portrayed in this work are Anger, Joy and Neutral in each of English, Marathi and Hindi languages. Different configurations of Artificial Neural Networks have been employed for classification purposes. The performance of the classifiers has been evaluated by False Negative Rate (FNR), False Positive Rate (FPR), True Positive Rate (TPR) and True Negative Rate (TNR).
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4942736