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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Suman Lata, Neha Kishore, Pardeep Sangwan
Μορφή: Άρθρο
Γλώσσα:English
Έκδοση: University of Kragujevac 2024-09-01
Σειρά:Proceedings on Engineering Sciences
Θέματα:
sentiments
long short-term memory network
speech emotion recognition
mel frequency cepstral coefficients
deep learning
Διαθέσιμο Online:https://pesjournal.net/journal/v6-n3/54.pdf

Διαδίκτυο

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

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