{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T17:29:04Z","timestamp":1772040544483,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811389498","type":"print"},{"value":"9789811389504","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,9,19]],"date-time":"2019-09-19T00:00:00Z","timestamp":1568851200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-981-13-8950-4_2","type":"book-chapter","created":{"date-parts":[[2019,9,18]],"date-time":"2019-09-18T13:04:58Z","timestamp":1568811898000},"page":"11-19","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Music Genre Classification Using Stacked Auto-Encoders"],"prefix":"10.1007","author":[{"given":"Michele","family":"Scarpiniti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simone","family":"Scardapane","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Danilo","family":"Comminiello","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aurelio","family":"Uncini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,9,19]]},"reference":[{"issue":"1","key":"2_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000006","volume":"2","author":"Y Bengio","year":"2009","unstructured":"Bengio, Y.: Learning deep architectures for AI. Found. Trends Mach. Learn. 2(1), 1\u2013127 (2009)","journal-title":"Found. Trends Mach. Learn."},{"key":"2_CR2","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/BF00332918","volume":"59","author":"H Bourlard","year":"1988","unstructured":"Bourlard, H., Kamp, Y.: Auto-association by multilayer perceptrons and singular value decomposition. Biol. Cybern. 59, 291\u2013294 (1988)","journal-title":"Biol. Cybern."},{"key":"2_CR3","unstructured":"Cast\u00e1n, D., Ortega, A.A.M., Lleida, E.: Audio segmentation-by-classification approach based on factor analysis in broadcast news domain. EURASIP J. Audio, Speech, Music. Process. 2014(34), 1\u201313 (2014)"},{"key":"2_CR4","unstructured":"Choi, K., Fazekas, G., Cho, K., Sandler, M.: A tutorial on deep learning for music information retrieval \n                    arXiv:1709.04396\n                    \n                   (2018)"},{"issue":"2","key":"2_CR5","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1109\/TMM.2010.2098858","volume":"13","author":"Z Fu","year":"2011","unstructured":"Fu, Z., Lu, G., Ting, K.M., Zhang, D.: A survey of audio-based music classification and annotation. IEEE Trans. Multimed. 13(2), 303\u2013319 (2011)","journal-title":"IEEE Trans. Multimed."},{"key":"2_CR6","unstructured":"Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. The MIT Press (2016)"},{"issue":"2","key":"2_CR7","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.eij.2012.03.001","volume":"13","author":"AJH Goulart","year":"2012","unstructured":"Goulart, A.J.H., Guido, R.C., Maciel, C.D.: Exploring different approaches for music genre classification. Egypt. Inform. J. 13(2), 59\u201363 (2012)","journal-title":"Egypt. Inform. J."},{"key":"2_CR8","unstructured":"Hinton, G.E., Zemel, R.S.: Autoencoders, minimum description length, and Helmholtz free energy. In: Proceeding of NIPS 1993 (1994)"},{"key":"2_CR9","unstructured":"Mandel, M., Ellis, D.: Song-level features and support vector machines for music classification. In: Proceeding of 6th International Symposium on Music Information Retrieval. London, UK (2005)"},{"issue":"2\u20133","key":"2_CR10","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/s10994-005-5824-7","volume":"58","author":"I Mierswa","year":"2005","unstructured":"Mierswa, I., Morik, K.: Automatic feature extraction for classifying audio data. Mach. Learn. 58(2\u20133), 127\u2013149 (2005)","journal-title":"Mach. Learn."},{"key":"2_CR11","unstructured":"Pampalk, E., Flexer, A., Widmer, G.: Improvements of audio based music similarity and genre classification? In: Proceeding of 6th International Symposium on Music Information Retrieval. London, UK (2005)"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Patsis, Y., Verhelst, W.: A speech\/music\/silence\/garbage\/ classifier for searching and indexing broadcast news material. In: Proceeding of 19th International Workshop on Database and Expert Systems Application (DEXA \u201908). Turin, Italy (2008)","DOI":"10.1109\/DEXA.2008.104"},{"key":"2_CR13","first-page":"254","volume-title":"Lecture Notes in Computer Science","author":"Soujanya Poria","year":"2013","unstructured":"Poria, S., Gelbukh, A., Hussain, A., Bandyopadhyay, S., Howard, N.: Music genre classification: A semi-supervised approach. In: Proceeding of the Mexican Conference on Pattern Recognition (MCPR 2013), pp. 254\u2013263 (2013)"},{"key":"2_CR14","doi-asserted-by":"crossref","unstructured":"Scardapane, S., Comminiello, D., Scarpiniti, M., Uncini, A.: Music classification using extreme learning machines. In: 8th International Symposium on Image and Signal Processing and Analysis (ISPA2013), pp. 377\u2013381. Trieste, Italy (2013)","DOI":"10.1109\/ISPA.2013.6703770"},{"issue":"2","key":"2_CR15","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1109\/MSP.2006.1598089","volume":"23","author":"N Scaringella","year":"2006","unstructured":"Scaringella, N., Zoia, G., Mlynek, D.: Automatic genre classification of music content: a survey. IEEE Signal Process. Mag. 23(2), 133\u2013141 (2006)","journal-title":"IEEE Signal Process. Mag."},{"key":"2_CR16","unstructured":"Shao, X., Xu, C., Kankanhalli, M.: Unsupervised classification of musical genre using hidden Markov model. In: IEEE International Conference of Multimedia Explore (ICME 2004). Taiwan (2004)"},{"key":"2_CR17","doi-asserted-by":"crossref","unstructured":"Silla, C.N., Kaestner, C.A., Koerich, A.L.: Automatic music genre classification using ensemble of classifiers. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 1687\u20131692 (2007)","DOI":"10.1109\/ICSMC.2007.4414136"},{"issue":"5","key":"2_CR18","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1109\/TSA.2002.800560","volume":"10","author":"G Tzanetakis","year":"2002","unstructured":"Tzanetakis, G., Cook, P.: Musical genre classification of audio signals. IEEE Trans. Speech Audio Process. 10(5), 293\u2013302 (2002)","journal-title":"IEEE Trans. Speech Audio Process."},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"Vavrek, J., Voz\u00e1rikov\u00e1, E., Pleva, M., Juh\u00e1r, J.: Broadcast news audio classification using SVM binary trees. In: Proceeding of the 35th International Conference on Telecommunications and Signal Processing (TSP 2012) (2012)","DOI":"10.1109\/TSP.2012.6256338"},{"key":"2_CR20","doi-asserted-by":"crossref","unstructured":"Vincent, P., Larochelle, H., Bengio, Y., Manzagol, P.A.: Extracting and composing robust features with denoising autoencoders. In: Proceedings of the Twenty-fifth International Conference on Machine Learning (ICML\u201908), pp. 1096\u20131103 (2008)","DOI":"10.1145\/1390156.1390294"},{"key":"2_CR21","first-page":"3371","volume":"11","author":"P Vincent","year":"2010","unstructured":"Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., Manzagol, P.A.: Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. J. Mach. Learn. Res. 11, 3371\u20133408 (2010)","journal-title":"J. Mach. Learn. Res."}],"container-title":["Smart Innovation, Systems and Technologies","Neural Approaches to Dynamics of Signal Exchanges"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-13-8950-4_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,18]],"date-time":"2019-09-18T13:05:25Z","timestamp":1568811925000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-13-8950-4_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,19]]},"ISBN":["9789811389498","9789811389504"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-13-8950-4_2","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"value":"2190-3018","type":"print"},{"value":"2190-3026","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,19]]},"assertion":[{"value":"19 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}