Music emotion recognition using deep Gaussian process

Sih Huei Chen, Yuan Shan Lee, Wen Chi Hsieh, Jia Ching Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

22 引文 斯高帕斯(Scopus)

摘要

Music is a powerful force that evokes human emotions. Several investigations of music emotion recognition (MER) have been conducted in recent years. This paper proposes a system for detecting emotion in music that is based on a deep Gaussian process (GP). The system consists of two parts-feature extraction and classification. In the feature extraction part, five types of features that are associated with emotions are selected for representing the music signal; these are rhythm, dynamics, timbre, pitch and tonality. A music clip is decomposed into frames and these features are extracted from each frame. Next, statistical values, such as mean and standard deviation, of frame-based features are calculated to generate a 38-dimensional feature vector. In the classification part, a deep GP is utilized for emotion recognition. We treat classification problem from the perspective of regression. Finally, 9 classes of emotion are categorized by 9 one-versus-all classifiers. The experimental results demonstrate that the proposed system performs well in emotion recognition.

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主出版物標題2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面495-498
頁數4
ISBN(電子)9789881476807
DOIs
出版狀態已出版 - 19 2月 2016
事件2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015 - Hong Kong, Hong Kong
持續時間: 16 12月 201519 12月 2015

出版系列

名字2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015

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???event.eventtypes.event.conference???2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
國家/地區Hong Kong
城市Hong Kong
期間16/12/1519/12/15

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