Emotion Recognition through Speech: A Review

Emotions are extremely important in human communication. Emotion is a way for people to communicate their feelings to other people. In Human-Computer Interaction (HCI), Speech Emotion Recognition (SER) has a vital role. Automated emotional recognition can help to improve the interaction between huma...

Full description

Saved in:

Bibliographic Details
Published in:	2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC) pp. 1150 - 1153
Main Authors:	Mahesh Yadav Konangi, Uma, Katreddy, Venkateswara Reddy, Rasula, Shiva Kumar, Marisa, Ganesh, Thakur, Tanima
Format:	Conference Proceeding
Language:	English
Published:	IEEE 09-05-2022
Subjects:	Artificial neural networks Emotion recognition Emotions feature extraction Hidden Markov Model Hidden Markov models Human computer interaction Mel-frequency cepstral coefficients Speech Emotion Recognition Speech recognition Support Vector Machine Support vector machine classification Voice activity detection
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Emotions are extremely important in human communication. Emotion is a way for people to communicate their feelings to other people. In Human-Computer Interaction (HCI), Speech Emotion Recognition (SER) has a vital role. Automated emotional recognition can help to improve the interaction between humans and computers, also reducing the need for human intervention. To extract emotions from signals, a variety of methodologies have been applied in S ER, which includes many classification techniques. This research study has analyzed various feature extraction approaches and classification algorithms. To extract different emotions from human speech data, classification approaches such as Hidden Markov Model (HMM), Gaussian Mixtures Model (GMM), Support Vector Machine (S VM), and Artificial Neural Network (ANN) are utilized.
DOI:	10.1109/ICAAIC53929.2022.9792710