Kannada Speech Emotion Recognition Using Ensembling Techniques

• Author(s): Smrithi Baliga; Sapna H M; Shreyas N; Yogesh Gowda V; Dr Chandrashekar M Patil; Prof. Audre Arlene
• Paper ID: 1704436
• Page: 250-255
• Published Date: 11-05-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 11 May-2023

Abstract

This study explores the development of a speech emotion recognition system for the Kannada language, using a dataset of audio recordings labeled with six emotion categories: happiness, sadness, anger, fear, and neutral. We used a combination of acoustic features and machine learning algorithms, including Mel-frequency cepstral coefficients (MFCCs), to classify emotions in the audio recordings. Our results show that the proposed system achieves an average accuracy of 75% on the Kannada emotion dataset, outperforming existing baseline models. These findings suggest that Kannada speech emotion recognition can be achieved with high accuracy using a combination of acoustic features and machine learning algorithms like RNN, CNN and DBN, paving the way for further research in this area.

Keywords

Speech Emotion Recognition, Mel-Frequency Cepstral Coefficients, Recurrent Neural Network, Deep Belief Network

Citations

IRE Journals:
Smrithi Baliga, Sapna H M, Shreyas N, Yogesh Gowda V, Dr Chandrashekar M Patil; Prof. Audre Arlene "Kannada Speech Emotion Recognition Using Ensembling Techniques" Iconic Research And Engineering Journals Volume 6 Issue 11 2023 Page 250-255

IEEE:
Smrithi Baliga, Sapna H M, Shreyas N, Yogesh Gowda V, Dr Chandrashekar M Patil; Prof. Audre Arlene "Kannada Speech Emotion Recognition Using Ensembling Techniques" Iconic Research And Engineering Journals, vol. 6, no. 11, May. 2023

APA:
Smrithi Baliga, Sapna H M, Shreyas N, Yogesh Gowda V, Dr Chandrashekar M Patil; Prof. Audre Arlene (2023). Kannada Speech Emotion Recognition Using Ensembling Techniques. Iconic Research And Engineering Journals, 6(11).

MLA:
Smrithi Baliga, Sapna H M, Shreyas N, Yogesh Gowda V, Dr Chandrashekar M Patil; Prof. Audre Arlene "Kannada Speech Emotion Recognition Using Ensembling Techniques" Iconic Research And Engineering Journals, vol. 6, no. 11, May. 2023.

BibTeX

@article{1704436,
author = {Smrithi Baliga, Sapna H M, Shreyas N, Yogesh Gowda V, Dr Chandrashekar M Patil; Prof. Audre Arlene},
title = {Kannada Speech Emotion Recognition Using Ensembling Techniques},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {6},
number = {11},
pages = {250-255},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1704436.pdf},
abstract = {This study explores the development of a speech emotion recognition system for the Kannada language, using a dataset of audio recordings labeled with six emotion categories: happiness, sadness, anger, fear, and neutral. We used a combination of acoustic features and machine learning algorithms, including Mel-frequency cepstral coefficients (MFCCs), to classify emotions in the audio recordings. Our results show that the proposed system achieves an average accuracy of 75% on the Kannada emotion dataset, outperforming existing baseline models. These findings suggest that Kannada speech emotion recognition can be achieved with high accuracy using a combination of acoustic features and machine learning algorithms like RNN, CNN and DBN, paving the way for further research in this area.},
keywords = {Speech Emotion Recognition, Mel-Frequency Cepstral Coefficients, Recurrent Neural Network, Deep Belief Network},
month = {May}
}