Study of Gender-Specific Emotion Expressivity in Speech Using MFCC and CNN

Analysis of sentiment is a pivotal component of natural language processing and has recently observed noteworthy evolutions. Still, the impact of gender on expressivity of the emotion remains an undiscovered area. The proposed work utilizes a broad range of over 12000 audio data samples from four di...

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Hlavní autoři:	Mayuri Bapat, Shankar M. Mali, Chandrashekhar Patil
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	University North 2026-01-01
Edice:	Tehnički Glasnik
Témata:	Convolution Neural Network (CNN) feature extraction Mel-Frequency Cepstral Coefficients (MFCC) vocal dimorphism
On-line přístup:	https://hrcak.srce.hr/file/503426
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