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Raphael, \u201cRelationshipsbetween lyrics and melody in popular music,\u201d Proc. International Society for Music Information Retrieval Conference (ISMIR 2009), pp.471-476, 2009."},{"key":"13","unstructured":"[13] E. Greene, T. Bodrumlu, and K. Knight, \u201cAutomatic analysis of rhythmic poetry with applications to generation and translation,\u201d Proc. 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP 2010), pp.524-533, 2010."},{"key":"14","unstructured":"[14] S. Reddy and K. Knight, \u201cUnsupervised discovery of rhyme schemes,\u201d Proc. 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2011), pp.77-82, 2011."},{"key":"15","unstructured":"[15] K. Watanabe, Y. Matsubayashi, N. Orita, N. Okazaki, K. Inui, S. Fukayama, T. Nakano, J. Smith, and M. Goto, \u201cModeling discourse segments in lyrics using repeated patterns,\u201d Proc. 26th International Conference on Computational Linguistics (COLING 2016), pp.1959-1969, 2016."},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] J.P.G. Mahedero, \u00c1. Mart\u00cdnez, P. Cano, M. Koppenberger, and F. Gouyon, \u201cNatural language processing of lyrics,\u201d Proc. 13th annual ACM international conference on Multimedia, pp.475-478, 2005. 10.1145\/1101149.1101255","DOI":"10.1145\/1101149.1101255"},{"key":"17","unstructured":"[17] M. Goto, H. Hashiguchi, T. Nishimura, and R. Oka, \u201cRWC music database: Popular, classical and jazz music databases,\u201d Proc. 3rd of International Society for Music Information Retrieval (ISMIR 2002), pp.287-288, 2002."},{"key":"18","unstructured":"[18] B.J. Grosz and C.L. Sidner, \u201cAttention, intentions, and the structure of discourse,\u201d Computational linguistics, vol.12, no.3, pp.175-204, 1986."},{"key":"19","unstructured":"[19] D.M. Blei, A.Y. Ng, and M.I. Jordan, \u201cLatent dirichlet allocation,\u201d Journal of Machine Learning Research, vol.3, pp.993-1022, 2003."},{"key":"20","unstructured":"[20] F. Kleedorfer, P. Knees, and T. Pohle, \u201cOh oh oh whoah! towards automatic topic detection in song lyrics,\u201d Proc. 9th International Society for Music Information Retrieval Conference (ISMIR 2008), pp.287-292, 2008."},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] W. Xu, X. Liu, and Y. Gong, \u201cDocument clustering based on non-negative matrix factorization,\u201d Proc. 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pp.267-273, 2003. 10.1145\/860435.860485","DOI":"10.1145\/860435.860485"},{"key":"22","unstructured":"[22] S. Sasaki, K. Yoshii, T. Nakano, M. Goto, and S. 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