{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T03:13:32Z","timestamp":1725851612890},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811004476"},{"type":"electronic","value":"9789811004483"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-981-10-0448-3_26","type":"book-chapter","created":{"date-parts":[[2016,3,19]],"date-time":"2016-03-19T03:34:03Z","timestamp":1458358443000},"page":"321-332","source":"Crossref","is-referenced-by-count":0,"title":["Audio Pattern Recognition and Mood Detection System"],"prefix":"10.1007","author":[{"family":"Priyanka Tyagi","sequence":"first","affiliation":[]},{"family":"Abhishek Mehrotra","sequence":"additional","affiliation":[]},{"family":"Shanu Sharma","sequence":"additional","affiliation":[]},{"family":"Sushil Kumar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,3,15]]},"reference":[{"key":"26_CR1","unstructured":"Ujlambkar, A., Upadhye, O., Deshpande, A., Suryawanshi, G.: Mood based music categorization system for bollywood music. Int. J. Adv. Comput. Res. 4(1, 14) (2014). ISSN (print): 2249-7277 ISSN (online): 2277-7970"},{"issue":"2","key":"26_CR2","doi-asserted-by":"crossref","first-page":"246","DOI":"10.2307\/1415746","volume":"48","author":"Kate Hevner","year":"1936","unstructured":"Hevner, K.: Experimental studies of the elements of expression in music. Am. J. Psychol. 48, 246\u2013268 (1936)","journal-title":"The American Journal of Psychology"},{"key":"26_CR3","unstructured":"Thayer, R.E.: The Biopsychology of Mood and Arousal. Oxford University Press, New York (1998)"},{"key":"26_CR4","doi-asserted-by":"crossref","unstructured":"Thayer, R.E.: The Origin of Everyday Moods: Managing Energy, Tension, and Stress. Oxford University Press, New York (1996)","DOI":"10.1093\/oso\/9780195087918.001.0001"},{"key":"26_CR5","unstructured":"McEnnis, D., McKay, C., Fujinaga, I., Depalle P.: jAudio: a feature extraction library. In: Proceedings of the International Conference on Music Information Retrieval, p. 6003 (2005)"},{"key":"26_CR6","unstructured":"Mitrovic, D., Zeppelzauer, M., Eidenberger, H.: Analysis of the data quality of audio descriptions of environmental sounds. J. Digital Inf. Manag. 5(2), 48 (2007)"},{"key":"26_CR7","unstructured":"Baum, D.: Emomusic\u2014classifying music according to emotional. In: Proceedings of the 7th Workshop on Data Analysis (WDA), Kosice, Slovakia (2006)"},{"key":"26_CR8","unstructured":"Dewi, K.C., Harjoko, A.: Kid\u2019s song classification based on mood parameters using K-nearest neighbor classification method and self organizing map. In: International Conference on Distributed Frameworks for Multi-media Applications (DFmA) (2010)"},{"key":"26_CR9","unstructured":"Li, T., Ogihara, M.: Detecting emotion in music. In: Proceedings of the International Symposium on Music Information Retrieval, Washington D.C., USA (2003)"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Dang, T.T., Shirai, K.: Machine learning approaches for mood classification of songs toward music search engine. In: International Conference on Knowledge and Systems Engineering (2009)","DOI":"10.1109\/KSE.2009.10"},{"key":"26_CR11","unstructured":"Liu, D., Lu, L., Zhang, H.J.: Automatic mood detection from acoustic music data. In: Conference: ISMIR 2003, 4th International Conference on Music Information Retrieval, Baltimore, Maryland, USA, October 27\u201330 (2003)"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Vyas, G., Dutta, M.L.: Automatic mood detection of indian music using MFCCs and K-means algorithm. In: Seventh International Conference on Contemporary Computing (IC3) (2014)","DOI":"10.1109\/IC3.2014.6897159"},{"key":"26_CR13","unstructured":"Hampiholi, V.: A method for music classification based on perceived mood detection for Indian bollywood music. World Acad. Sci. Eng. Technol. 6, 12\u201325 (2012)"},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Bhat, A.S., Amith, V.S., Prasad, N.S.: An efficient classification algorithm for music mood detection in Western and Hindi music using audio feature extraction. In: 2014 Fifth International Conference on Signals and Image Processing","DOI":"10.1109\/ICSIP.2014.63"},{"issue":"6","key":"26_CR15","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1109\/TMM.2005.858380","volume":"7","author":"J.-J. Aucouturier","year":"2005","unstructured":"Aucouturier, J.-J., Pachet, F., Sandler, M.: The way it sounds: timbre models for analysis and retrieval of music signals. IEEE Trans. Multimedia 7(6) (2005)","journal-title":"IEEE Transactions on Multimedia"},{"key":"26_CR16","unstructured":"Singh, P., Kapoor, A., Kaushik, V., Maringanti, H.B.: Architecture for automated tagging and clustering of song files according to mood. IJCSI Int. J. Comput. Sci. 7(4, 2) (2010)"},{"issue":"1","key":"26_CR17","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"Mark Hall","year":"2009","unstructured":"Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD Explor. 11(1) (2009)","journal-title":"ACM SIGKDD Explorations Newsletter"}],"container-title":["Advances in Intelligent Systems and Computing","Proceedings of Fifth International Conference on Soft Computing for Problem Solving"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-10-0448-3_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,15]],"date-time":"2024-06-15T04:08:04Z","timestamp":1718424484000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-10-0448-3_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9789811004476","9789811004483"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-10-0448-3_26","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2016]]}}}