{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T11:21:02Z","timestamp":1761218462682,"version":"build-2065373602"},"reference-count":24,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T00:00:00Z","timestamp":1645660800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Several studies have shown that music can reduce unpleasant emotions. Based on the results of this research, several systems have been proposed to suggest songs that match the emotions of the audience. As a part of the system, we aim to develop a method that can infer the emotional value of a song from its Japanese lyrics with higher accuracy, by applying the technology of inferring the emotions expressed in sentences. In addition to matching with a basic emotion dictionary, we use a Web search engine to evaluate the sentiment of words that are not included in the dictionary. As a further improvement, as a pre-processing of the input to the system, the system corrects the omissions of the following verbs or particles and inverted sentences, which are frequently used in Japanese lyrics, into normal sentences. We quantitatively evaluate the degree to which these processes improve the emotion estimation system. The results show that the preprocessing could improve the accuracy by about 4%. Japanese lyrics contain many informal sentences such as inversions. We pre-processed these sentences into formal sentences and investigated the effect of the pre-processing on the emotional inference of the lyrics. The results show that the preprocessing may improve the accuracy of emotion estimation.<\/jats:p>","DOI":"10.3390\/s22051800","type":"journal-article","created":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T21:11:07Z","timestamp":1645737067000},"page":"1800","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Estimating the Emotional Information in Japanese Songs Using Search Engines"],"prefix":"10.3390","volume":"22","author":[{"given":"Jin","family":"Akaishi","sequence":"first","affiliation":[{"name":"Department of Human-Oriented Information Systems Engineering, National Institute of Technology, Kumamoto College, 2659-2 Suya, Koshi 861-1102, Kumamoto, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masaki","family":"Sakata","sequence":"additional","affiliation":[{"name":"School of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo 060-8628, Hokkaido, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jouichiro","family":"Yoshinaga","sequence":"additional","affiliation":[{"name":"Nisshin Electronics Service Co., Ltd., Tokyo Skytree East Tower F15, 1-1-2, Oshiage, Sumida-ku, Tokyo 131-0045, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mitsutaka","family":"Nakano","sequence":"additional","affiliation":[{"name":"Department of Human-Oriented Information Systems Engineering, National Institute of Technology, Kumamoto College, 2659-2 Suya, Koshi 861-1102, Kumamoto, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazuhiro","family":"Koshi","sequence":"additional","affiliation":[{"name":"Department of Human-Oriented Information Systems Engineering, National Institute of Technology, Kumamoto College, 2659-2 Suya, Koshi 861-1102, Kumamoto, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7435-6638","authenticated-orcid":false,"given":"Kimiyasu","family":"Kiyota","sequence":"additional","affiliation":[{"name":"Department of Human-Oriented Information Systems Engineering, National Institute of Technology, Kumamoto College, 2659-2 Suya, Koshi 861-1102, Kumamoto, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1177\/0044118X91023001004","article-title":"Adolescents and heavy metal music: From mouth to metalheads","volume":"23","author":"Arnett","year":"1991","journal-title":"Youth Soc."},{"key":"ref_2","first-page":"445","article-title":"The emotional use of popular music by adolescents","volume":"68","author":"Wells","year":"1991","journal-title":"J. Mass Commun. Q."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"43","DOI":"10.2307\/40285811","article-title":"A cross-cultural investigation of the perception of emotion in music: Psychophysical and cultural cues","volume":"17","author":"Balkwill","year":"1999","journal-title":"Music Percept."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"23","DOI":"10.5926\/jjep1953.50.1_23","article-title":"Why People Listen to Sad Music: Effects of Music on Sad Moods","volume":"50","author":"Matsumoto","year":"2002","journal-title":"Jpn. J. Educ. Psychol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"272","DOI":"10.3389\/fnhum.2015.00272","article-title":"Extreme metal music and anger processing","volume":"9","author":"Sharman","year":"2015","journal-title":"Front. Hum. Neurosci."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Furuya, M., Huang, H., and Kawagoe, K. (2014, January 7\u20139). Music classification method based on lyrics for music therapy. Proceedings of the 18th International Database Engineering & Applications Symposium, Porto, Portugal.","DOI":"10.1145\/2628194.2628203"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"960","DOI":"10.1037\/0022-3514.84.5.960","article-title":"Exposure to Violent Media: The Effects of Songs with Violent Lyrics on Aggressive Thoughts and Feelings","volume":"84","author":"Anderson","year":"2016","journal-title":"J. Personal. Soc. Psychol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1177\/0305735606067168","article-title":"Songs and emotions: Are lyrics and melodies equal partners?","volume":"34","author":"Ali","year":"2006","journal-title":"Psychol. Music"},{"key":"ref_9","unstructured":"Kim, Y.E., Schmidt, E.M., Migneco, R., Morton, B.G., Richardson, P., Scott, J., Speck, J.A., and Turnbull, D. (2010, January 9\u201313). Music emotion recognition: A state of the art review. Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR 2010), Utrecht, The Netherlands."},{"key":"ref_10","unstructured":"McVicar, M., Freeman, T., and Bie, T.D. (2011, January 24\u201328). Mining the Correlation between lyrical and audio features and the emergence of mood. Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), Miami, FL, USA."},{"key":"ref_11","unstructured":"Mihalcea, R., and Strapparava, C. (2012, January 12\u201314). Lyrics, music, and emotions. Proceedings of the 2012 Joint Conference on Empirical Methods in Natrual Language Processing and Computational Natural Language Learning, Jeju city, Korea."},{"key":"ref_12","unstructured":"Bradley, M., and Lang, P. (1999). Affective Norms for English Words (ANEW): Instruction Manual and Affective Ratings, Center for Research in Psychophysiology, University of Florida. Technical Report."},{"key":"ref_13","unstructured":"Hu, Y., Chen, X., and Yang, D. (2009, January 26\u201330). Lyric-based song emotion detection with affective lexicon and fuzzy clustering method. Proceedings of the 10th International Society for Music Information Retrieval Conference (ISMIR 2009), Kobe, Japan."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Matsumoto, K., and Sasayama, M. (2018, January 7\u201310). Lyric emotion estimation using word embedding learned from lyric corpus. Proceedings of the IEEE 4th International Conference on Computer and Communications (ICCC), Chengdu, China.","DOI":"10.1109\/CompComm.2018.8780811"},{"key":"ref_15","first-page":"1","article-title":"Emotion Detection and Sentiment Analysis in Text Corpus: A Differential Study with Informal and Formal Writing Styles","volume":"101","author":"Kaur","year":"2014","journal-title":"Int. J. Comput. Appl."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yang, D., and Lee, W. (2009, January 14\u201316). Music emotion identification from lyrics. Proceedings of the 11th IEEE International Symposium on Multimedia, San Diego, CA, USA.","DOI":"10.1109\/ISM.2009.123"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1142\/S1793840608001950","article-title":"Sentiment Vector Space Model for Lyric-Based Song Sentiment Classification","volume":"21","author":"Xia","year":"2008","journal-title":"Int. J. Comput. Process. Lang."},{"key":"ref_18","first-page":"30","article-title":"A System for Affect Analysis of Utterances in Japanese Supported with Web Mining","volume":"21","author":"Ptaszynski","year":"2009","journal-title":"J. Jpn. Soc. Fuzzy Theory Intell. Inform."},{"key":"ref_19","unstructured":"Shi, W., Rzepka, R., and Araki, K. (2008, January 2\u20134). Emotive information discovery from user textual input using causal associations from the internet. Proceedings of the Forum on Information Technology 2008, Fujisawa, Japan."},{"key":"ref_20","unstructured":"Akaishi, J., Sakata, M., Nakano, M., Koshi, K., and Kiyota, K. (2021, January 17\u201320). Estimating the emotional information in songs using search engines. Proceedings of the 14th International Symposium on Advances in Technology Education, Turku, Finland."},{"key":"ref_21","unstructured":"Nakamura, A. (2005). Emotional Display Dictionary, Sanseido."},{"key":"ref_22","unstructured":"Yamada, A. (2011). Suggestion of the Feelings Extraction Method of the Song Using the Lyrics Information. [Bachelor Graduation Thesis, Konan University]. (In Japanese)."},{"key":"ref_23","unstructured":"Takebe, Y. (2010). Must-Have Synonyms Practical Dictionary, Sanseido."},{"key":"ref_24","unstructured":"(2021, December 23). MeCab: Yet Another Part-of-Speech and Morphological Analyzer. Available online: https:\/\/taku910.github.io\/mecab\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/5\/1800\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:26:56Z","timestamp":1760135216000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/5\/1800"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,24]]},"references-count":24,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["s22051800"],"URL":"https:\/\/doi.org\/10.3390\/s22051800","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,2,24]]}}}