SENTIMENT ANALYSIS ON SPEECH SIGNALS: LEVERAGING MFCC-LSTM TECHNIQUE FOR ENHANCED EMOTIONAL UNDERSTANDING

SENTIMENT ANALYSIS ON SPEECH SIGNALS: LEVERAGING MFCC-LSTM TECHNIQUE FOR ENHANCED EMOTIONAL UNDERSTANDING

The analysis of emotions expressed in spoken language holds a pivotal role in human communication, artificial intelligence, and human-computer interaction. While emotion recognition in text has seen considerable advancements, recognizing emotional states in spoken speech presents distinct challenges...

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Bibliographic Details
Main Authors: Suman Lata, Neha Kishore, Pardeep Sangwan
Format: Article
Language:English
Published: University of Kragujevac 2024-09-01
Series:Proceedings on Engineering Sciences
Subjects:
sentiments
long short-term memory network
speech emotion recognition
mel frequency cepstral coefficients
deep learning
Online Access:https://pesjournal.net/journal/v6-n3/54.pdf

Internet

https://pesjournal.net/journal/v6-n3/54.pdf

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