JOURNAL ARTICLE

Speech Emotion Recognition Using Machine Learning

Abstract

In the field of human-computer interaction, identifying the emotions conveyed in a person's speech is a challenge that is both incredibly fascinating and challenging. Recent times have seen a significant uptick in people's interest in this topic. In the subject of speech emotion recognition, a wide variety of techniques have been applied in order to extract emotions from signals. These techniques include a number of well-known speech analysis and classification strategies. This paper provides an overview of the deep learning technique, which is based on a simple algorithm based on feature extraction and model creation that recognizes emotion. In the traditional method of speech emotion recognition, features are first extracted from the speech signals, then the features themselves are picked, collectively known as the selection module, and then the emotions are recognized.

Keywords:
Computer science Emotion recognition Variety (cybernetics) Speech recognition Feature extraction Field (mathematics) Artificial intelligence Feature selection Selection (genetic algorithm) Subject (documents) Natural language processing Feature (linguistics) Speech processing Affective computing Linguistics

Metrics

7
Cited By
2.50
FWCI (Field Weighted Citation Impact)
19
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Emotion and Mood Recognition
Social Sciences →  Psychology →  Experimental and Cognitive Psychology
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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