Gender dependent word-level emotion detection using global spectral speech features

In this study, global spectral features extracted from word and sentence levels are studied for speech emotion recognition. MFCC (Mel Frequency Cepstral Coefficient) were used as spectral information for recognition purpose. Global spectral features representing gross statistics such as mean of MFCC...

詳細記述

書誌詳細
第一著者: Siddique, Haris
フォーマット: 学位論文
言語:英語
英語
出版事項: 2015
主題:
オンライン・アクセス:https://etd.uum.edu.my/4518/1/s814534.pdf
https://etd.uum.edu.my/4518/2/s814534_abstract.pdf
https://etd.uum.edu.my/4518/
Abstract Abstract here