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Music Theory-Inspired Acoustic Representation for Speech Emotion Recognition
Li, Xingfeng1; Shi, Xiaohan2; Hu, Desheng3; Li, Yongwei4; Zhang, Qingchen1; Wang, Zhengxia5; Unoki, Masashi6; Akagi, Masato6
Source PublicationIEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
ISSN2329-9290
2023
Volume31Pages:2534-2547
Corresponding AuthorLi, Xingfeng(lixingfeng@hainanu.edu.cn)
AbstractThis research presents a music theory-inspired acoustic representation (hereafter, MTAR) to address improved speech emotion recognition. The recognition of emotion in speech and music is developed in parallel, yet a relatively limited understanding of MTAR for interpreting speech emotions is involved. In the present study, we use music theory to study representative acoustics associated with emotion in speech from vocal emotion expressions and auditory emotion perception domains. In experiments assessing the role and effectiveness of the proposed representation in classifying discrete emotion categories and predicting continuous emotion dimensions, it shows promising performance compared with extensively used features for emotion recognition based on the spectrogram, Mel-spectrogram, Mel-frequency cepstral coefficients, VGGish, and the large baseline feature sets of the INTERSPEECH challenges. This proposal opens up a novel research avenue in developing a computational acoustic representation of speech emotion via music theory.
KeywordAffective computing speech emotion recognition acoustic representation music theory and speech analysis
DOI10.1109/TASLP.2023.3289312
WOS KeywordPERCEPTION ; EXPRESSION ; PATTERNS ; FEATURES ; PITCH ; PERSPECTIVE ; MODALITIES ; KNOWLEDGE ; INTERVALS ; COGNITION
Indexed BySCI
Language英语
Funding ProjectKey Research and Development Program of Hainan Province[ZDYF2021GXJS017] ; National Natural Science Foundation of China[82160345] ; National Natural Science Foundation of China[62201571] ; Key Science and Technology Plan Project of Haikou[2021-016]
Funding OrganizationKey Research and Development Program of Hainan Province ; National Natural Science Foundation of China ; Key Science and Technology Plan Project of Haikou
WOS Research AreaAcoustics ; Engineering
WOS SubjectAcoustics ; Engineering, Electrical & Electronic
WOS IDWOS:001025466100003
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/53769
Collection多模态人工智能系统全国重点实验室_智能交互
Corresponding AuthorLi, Xingfeng
Affiliation1.Hainan Univ, Grad Sch Comp Sci & Technol, Haikou 570288, Peoples R China
2.Nagoya Univ, Sch Informat Sci, Nagoya 4648601, Japan
3.Taiyuan Univ Technol, Coll Informat & Comp, Taiyuan 030024, Peoples R China
4.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
5.Hainan Univ, Sch Comp Sci & Technol, Haikou 570288, Peoples R China
6.Japan Adv Inst Sci & Technol, Sch Informat Sci, Nomi 9231292, Japan
Recommended Citation
GB/T 7714
Li, Xingfeng,Shi, Xiaohan,Hu, Desheng,et al. Music Theory-Inspired Acoustic Representation for Speech Emotion Recognition[J]. IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,2023,31:2534-2547.
APA Li, Xingfeng.,Shi, Xiaohan.,Hu, Desheng.,Li, Yongwei.,Zhang, Qingchen.,...&Akagi, Masato.(2023).Music Theory-Inspired Acoustic Representation for Speech Emotion Recognition.IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,31,2534-2547.
MLA Li, Xingfeng,et al."Music Theory-Inspired Acoustic Representation for Speech Emotion Recognition".IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 31(2023):2534-2547.
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