{"title":"Associations between lyric and musical depth in Chinese songs: Evidence from computational modeling.","authors":"Liang Xu, Bingfei Xu, Zaoyi Sun, Hongting Li","doi":"10.1002/pchj.785","DOIUrl":null,"url":null,"abstract":"<p><p>Musical depth, which encompasses the intellectual and emotional complexity of music, is a robust dimension that influences music preference. However, there remains a dearth of research exploring the relationship between lyrics and musical depth. This study addressed this gap by analyzing linguistic inquiry and word count-based lyric features extracted from a comprehensive dataset of 2372 Chinese songs. Correlation analysis and machine learning techniques revealed compelling connections between musical depth and various lyric features, such as the usage frequency of emotion words, time words, and insight words. To further investigate these relationships, prediction models for musical depth were constructed using a combination of audio and lyric features as inputs. The results demonstrated that the random forest regressions (RFR) that integrated both audio and lyric features yielded superior prediction performance compared to those relying solely on lyric inputs. Notably, when assessing the feature importance to interpret the RFR models, it became evident that audio features played a decisive role in predicting musical depth. This finding highlights the paramount significance of melody over lyrics in effectively conveying the intricacies of musical depth.</p>","PeriodicalId":20804,"journal":{"name":"PsyCh journal","volume":" ","pages":"915-926"},"PeriodicalIF":1.3000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11608776/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PsyCh journal","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1002/pchj.785","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/19 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Musical depth, which encompasses the intellectual and emotional complexity of music, is a robust dimension that influences music preference. However, there remains a dearth of research exploring the relationship between lyrics and musical depth. This study addressed this gap by analyzing linguistic inquiry and word count-based lyric features extracted from a comprehensive dataset of 2372 Chinese songs. Correlation analysis and machine learning techniques revealed compelling connections between musical depth and various lyric features, such as the usage frequency of emotion words, time words, and insight words. To further investigate these relationships, prediction models for musical depth were constructed using a combination of audio and lyric features as inputs. The results demonstrated that the random forest regressions (RFR) that integrated both audio and lyric features yielded superior prediction performance compared to those relying solely on lyric inputs. Notably, when assessing the feature importance to interpret the RFR models, it became evident that audio features played a decisive role in predicting musical depth. This finding highlights the paramount significance of melody over lyrics in effectively conveying the intricacies of musical depth.
期刊介绍:
PsyCh Journal, China''s first international psychology journal, publishes peer‑reviewed research articles, research reports and integrated research reviews spanning the entire spectrum of scientific psychology and its applications. PsyCh Journal is the flagship journal of the Institute of Psychology, Chinese Academy of Sciences – the only national psychology research institute in China – and reflects the high research standards of the nation. Launched in 2012, PsyCh Journal is devoted to the publication of advanced research exploring basic mechanisms of the human mind and behavior, and delivering scientific knowledge to enhance understanding of culture and society. Towards that broader goal, the Journal will provide a forum for academic exchange and a “knowledge bridge” between China and the World by showcasing high-quality, cutting-edge research related to the science and practice of psychology both within and outside of China. PsyCh Journal features original articles of both empirical and theoretical research in scientific psychology and interdisciplinary sciences, across all levels, from molecular, cellular and system, to individual, group and society. The Journal also publishes evaluative and integrative review papers on any significant research contribution in any area of scientific psychology