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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/17070

Title: On The Differences Between Song and Speech Emotion Recognition: Effect of Feature Sets, Feature Types, and Classifiers
Authors: Atmaja, Bagus Tris
Akagi, Masato
Keywords: Song emotion recognition
speech emotion recognition
acoustic features
emotion classifiers
affective computing
Issue Date: 2020-11-18
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: 2020 IEEE REGION 10 CONFERENCE (TENCON)
Start page: 968
End page: 972
DOI: 10.1109/TENCON50793.2020.9293852
Abstract: In this paper, we argue that singing voice (song) is more emotional than speech. We evaluate different features sets, feature types, and classifiers on both song and speech emotion recognition. Three feature sets: GeMAPS, pyAudioAnalysis, and LibROSA; two feature types, low-level descriptors and high-level statistical functions; and four classifiers: multilayer perceptron, LSTM, GRU, and convolution neural networks; are examined on both songand speech data with the same parameter values. The results show no remarkable difference between song and speech data on using the same method. Comparisons of two results reveal that song is more emotional than speech. In addition, high-level statistical functions of acoustic features gained higher performance than low-level descriptors in this classification task. This result strengthens the previous finding on the regression task which reported the advantage use of high-level features.
Rights: This is the author's version of the work. Copyright (C) 2020 IEEE. 2020 IEEE REGION 10 CONFERENCE (TENCON), 2020, pp.968-972. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/10119/17070
Material Type: author
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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