{"title":"音乐元素与情感关系的跨文化分析","authors":"Xin Wang, Yujia Wei, Dasheng Yang","doi":"10.1049/ccs2.12032","DOIUrl":null,"url":null,"abstract":"<p>In a cross-cultural context, exploring musical elements' cultural specificity and universality that affect various types of music is conducive to personalised emotion recognition. In this study, high-level musical elements are introduced to explore their influence on emotional perception. By comparing music emotion recognition (MER) models of varied cultural music, musical elements with cultural universality and cultural specificity are further determined. Participants rated valence, tension arousal, and energy arousal on labelled nine-point analogical–categorical scales for four types of classical music: Chinese ensemble, Chinese solo, Western ensemble, and Western solo. Fifteen musical elements in five categories—timbre, rhythm, articulation, dynamics, and register were annotated through manual evaluation or the automatic algorithm. The relationship between music emotion and musical elements was analysed through partial least squares regression. Results showed that tempo, rhythm complexity, and articulation are culturally universal; musical elements related to timbre, register, and dynamics features are culturally specific. By increasing tempo, rhythm complexity, staccato, perception of valence, tension arousal, and energy arousal can be effectively improved. Based on the Partial least squares regression (PLSR) model's results for the datasets, the combination of manual and automatic annotation for musical elements can improve the MER system's performance.</p>","PeriodicalId":33652,"journal":{"name":"Cognitive Computation and Systems","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs2.12032","citationCount":"2","resultStr":"{\"title\":\"Cross-cultural analysis of the correlation between musical elements and emotion\",\"authors\":\"Xin Wang, Yujia Wei, Dasheng Yang\",\"doi\":\"10.1049/ccs2.12032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In a cross-cultural context, exploring musical elements' cultural specificity and universality that affect various types of music is conducive to personalised emotion recognition. In this study, high-level musical elements are introduced to explore their influence on emotional perception. By comparing music emotion recognition (MER) models of varied cultural music, musical elements with cultural universality and cultural specificity are further determined. Participants rated valence, tension arousal, and energy arousal on labelled nine-point analogical–categorical scales for four types of classical music: Chinese ensemble, Chinese solo, Western ensemble, and Western solo. Fifteen musical elements in five categories—timbre, rhythm, articulation, dynamics, and register were annotated through manual evaluation or the automatic algorithm. The relationship between music emotion and musical elements was analysed through partial least squares regression. Results showed that tempo, rhythm complexity, and articulation are culturally universal; musical elements related to timbre, register, and dynamics features are culturally specific. By increasing tempo, rhythm complexity, staccato, perception of valence, tension arousal, and energy arousal can be effectively improved. Based on the Partial least squares regression (PLSR) model's results for the datasets, the combination of manual and automatic annotation for musical elements can improve the MER system's performance.</p>\",\"PeriodicalId\":33652,\"journal\":{\"name\":\"Cognitive Computation and Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2021-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ccs2.12032\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Computation and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/ccs2.12032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Computation and Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ccs2.12032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Cross-cultural analysis of the correlation between musical elements and emotion
In a cross-cultural context, exploring musical elements' cultural specificity and universality that affect various types of music is conducive to personalised emotion recognition. In this study, high-level musical elements are introduced to explore their influence on emotional perception. By comparing music emotion recognition (MER) models of varied cultural music, musical elements with cultural universality and cultural specificity are further determined. Participants rated valence, tension arousal, and energy arousal on labelled nine-point analogical–categorical scales for four types of classical music: Chinese ensemble, Chinese solo, Western ensemble, and Western solo. Fifteen musical elements in five categories—timbre, rhythm, articulation, dynamics, and register were annotated through manual evaluation or the automatic algorithm. The relationship between music emotion and musical elements was analysed through partial least squares regression. Results showed that tempo, rhythm complexity, and articulation are culturally universal; musical elements related to timbre, register, and dynamics features are culturally specific. By increasing tempo, rhythm complexity, staccato, perception of valence, tension arousal, and energy arousal can be effectively improved. Based on the Partial least squares regression (PLSR) model's results for the datasets, the combination of manual and automatic annotation for musical elements can improve the MER system's performance.