Speech emotion classification using multiple kernel Gaussian process

Sih Huei Chen, Jia Ching Wang, Wen Chi Hsieh, Yu Hao Chin, Chin Wen Ho, Chung Hsien Wu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

6 引文 斯高帕斯(Scopus)

摘要

Given the increasing attention paid to speech emotion classification in recent years, this work presents a novel speech emotion classification approach based on the multiple kernel Gaussian process. Two major aspects of a classification problem that play an important role in classification accuracy are addressed, i.e. feature extraction and classification. Prosodic features and other features widely used in sound effect classification are selected. A semi-nonnegative matrix factorization algorithm is then applied to the proposed features in order to obtain more information about the features. Following feature extraction, a multiple kernel Gaussian process (GP) is used for classification, in which two similarity notions from our data in the learning algorithm are presented by combining the linear kernel and radial basis function (RBF) kernel. According to our results, the proposed speech emotion classification apporach achieve an accuracy of 77.74%. Moreover, comparing different apporaches reveals that the proposed system performs best than other apporaches.

原文???core.languages.en_GB???
主出版物標題2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9789881476821
DOIs
出版狀態已出版 - 17 1月 2017
事件2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 - Jeju, Korea, Republic of
持續時間: 13 12月 201616 12月 2016

出版系列

名字2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016

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???event.eventtypes.event.conference???2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
國家/地區Korea, Republic of
城市Jeju
期間13/12/1616/12/16

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