文章基本信息

标题：Acoustic Emotion Recognition Using Linear and Nonlinear Cepstral Coefficients
本地全文：下载
作者：Farah Chenchah ; Zied Lachiri
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2015
卷号：6
期号：11
DOI：10.14569/IJACSA.2015.061119
出版社：Science and Information Society (SAI)
摘要：Recognizing human emotions through vocal channel has gained increased attention recently. In this paper, we study how used features, and classifiers impact recognition accuracy of emotions present in speech. Four emotional states are considered for classification of emotions from speech in this work. For this aim, features are extracted from audio characteristics of emotional speech using Linear Frequency Cepstral Coefficients (LFCC) and Mel-Frequency Cepstral Coefficients (MFCC). Further, these features are classified using Hidden Markov Model (HMM) and Support Vector Machine (SVM).
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Mel Frequency Cepstral Coefficients (MFCC); Linear Frequency Cepstral Coefficients (LFCC);Hidden Markov Model (HMM); Support Vector Machine (SVM); emotion recognition