{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T07:54:49Z","timestamp":1764402889404,"version":"3.37.3"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2018,11,20]],"date-time":"2018-11-20T00:00:00Z","timestamp":1542672000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100007242","name":"\u00c9cole Polytechnique, Universit\u00e9 Paris-Saclay","doi-asserted-by":"publisher","award":["AMX"],"award-info":[{"award-number":["AMX"]}],"id":[{"id":"10.13039\/501100007242","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1007\/s00521-018-3868-4","type":"journal-article","created":{"date-parts":[[2018,11,20]],"date-time":"2018-11-20T10:33:42Z","timestamp":1542710022000},"page":"995-1005","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Anticipation-RNN: enforcing unary constraints in sequence generation, with application to interactive music generation"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1462-6103","authenticated-orcid":false,"given":"Ga\u00ebtan","family":"Hadjeres","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frank","family":"Nielsen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,20]]},"reference":[{"key":"3868_CR1","doi-asserted-by":"publisher","DOI":"10.1090\/mmono\/191","volume-title":"Methods of information geometry","author":"Si Amari","year":"2007","unstructured":"Amari Si, Nagaoka H (2007) Methods of information geometry, vol 191. American Mathematical Society, Providence"},{"issue":"3","key":"3868_CR2","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1525\/jams.2016.69.3.699","volume":"69","author":"Y Balmer","year":"2016","unstructured":"Balmer Y, Lac\u00f4te T, Murray CB (2016) Messiaen the borrower: recomposing Debussy through the deforming prism. J Am Musicol Soc 69(3):699\u2013791. \nhttps:\/\/doi.org\/10.1525\/jams.2016.69.3.699","journal-title":"J Am Musicol Soc"},{"issue":"4","key":"3868_CR3","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1016\/0165-1684(89)90079-0","volume":"18","author":"M Basseville","year":"1989","unstructured":"Basseville M (1989) Distance measures for signal processing and pattern recognition. Signal Process 18(4):349\u2013369","journal-title":"Signal Process"},{"key":"3868_CR4","unstructured":"Berglund M, Raiko T, Honkala M, K\u00e4rkk\u00e4inen L, Vetek A, Karhunen J (2015) Bidirectional recurrent neural networks as generative models\u2014reconstructing gaps in time series. ArXiv e-prints \n1504:01575"},{"key":"3868_CR5","unstructured":"Boulanger-lewandowski N, Bengio Y, Vincent P (2012) Modeling temporal dependencies in high-dimensional sequences: application to polyphonic music generation and transcription. In: Proceedings of the 29th international conference on machine learning (ICML-12), pp 1159\u20131166"},{"key":"3868_CR6","unstructured":"Boulanger-Lewandowski N, Bengio Y, Vincent P (2012) Modeling temporal dependencies in high-dimensional sequences: application to polyphonic music generation and transcription. In: Proceedings of the 29th international conference on machine learning (ICML-12), Edinburgh, Scotland, UK, pp 1159\u20131166"},{"key":"3868_CR7","doi-asserted-by":"publisher","unstructured":"Colombo F, Seeholzer A, Gerstner W (2017) Deep artificial composer: a creative neural network model for automated melody generation. In: Computational intelligence in music, sound, art and design: 6th international conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19\u201321, 2017, Proceedings. Springer, Cham, pp 81\u201396. \nhttps:\/\/doi.org\/10.1007\/978-3-319-55750-2-6","DOI":"10.1007\/978-3-319-55750-2-6"},{"key":"3868_CR8","unstructured":"Cuthbert MS, Ariza C (2010) music21: a toolkit for computer-aided musicology and symbolic music data. International Society for Music Information Retrieval"},{"key":"3868_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-642-00234-2","volume-title":"Encyclopedia of Distances","author":"Michel Marie Deza","year":"2009","unstructured":"Deza MM, Deza E (2009) Encyclopedia of distances. In: Encyclopedia of distances. Springer, Berlin, pp 1\u2013583"},{"key":"3868_CR10","unstructured":"Goodfellow I, Bengio Y, Courville A (2016) Deep learning. MIT Press, London"},{"key":"3868_CR11","first-page":"5","volume-title":"Studies in Computational Intelligence","author":"Alex Graves","year":"2012","unstructured":"Graves A (2012) Supervised sequence labelling. In: Supervised sequence labelling with recurrent neural networks. Springer, Berlin, pp 5\u201313"},{"key":"3868_CR12","unstructured":"Hadjeres G, Sakellariou J, Pachet F (2016) Style imitation and chord invention in polyphonic music with exponential families. CoRR \narxiv: abs\/1609.05152"},{"key":"3868_CR13","unstructured":"Hadjeres G, Pachet F, Nielsen F (2017) DeepBach: a steerable model for Bach chorales generation. In: Proceedings of the 34th international conference on machine learning. ICML 2017, Sydney, NSW, Australia, 6\u201311 August 2017, pp 1362\u20131371. \nhttp:\/\/proceedings.mlr.press\/v70\/hadjeres17a.html"},{"issue":"5","key":"3868_CR14","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1145\/3108242","volume":"50","author":"D Herremans","year":"2017","unstructured":"Herremans D, Chuan CH, Chew E (2017) A functional taxonomy of music generation systems. ACM Comput Surv (CSUR) 50(5):69","journal-title":"ACM Comput Surv (CSUR)"},{"issue":"8","key":"3868_CR15","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"key":"3868_CR16","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv preprint \narXiv:14126980"},{"key":"3868_CR17","unstructured":"Lattner S, Grachten M, Widmer G (2016) Imposing higher-level structure in polyphonic music generation using convolutional restricted boltzmann machines and constraints. \nArXiv:1612.04742v2"},{"key":"3868_CR18","unstructured":"Lee JY, Wick M, Tristan J, Carbonell JG (2017) Enforcing constraints on outputs with unconstrained inference. CoRR \narxiv: abs\/1707.08608"},{"key":"3868_CR19","unstructured":"Liang F (2016) BachBot: automatic composition in the style of Bach chorales"},{"issue":"8","key":"3868_CR20","doi-asserted-by":"publisher","first-page":"5455","DOI":"10.1109\/TIT.2011.2159046","volume":"57","author":"F Nielsen","year":"2011","unstructured":"Nielsen F, Boltz S (2011) The Burbea\u2013Rao and Bhattacharyya centroids. IEEE Trans Inf Theory 57(8):5455\u20135466","journal-title":"IEEE Trans Inf Theory"},{"issue":"3","key":"3868_CR21","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1007\/BF02517812","volume":"55","author":"F \u00d6sterreicher","year":"2003","unstructured":"\u00d6sterreicher F, Vajda I (2003) A new class of metric divergences on probability spaces and its applicability in statistics. Ann Inst Stat Math 55(3):639\u2013653. \nhttps:\/\/doi.org\/10.1007\/BF02517812","journal-title":"Ann Inst Stat Math"},{"key":"3868_CR22","doi-asserted-by":"crossref","unstructured":"Papadopoulos A, Pachet F, Roy P, Sakellariou J (2015) Exact sampling for regular and Markov constraints with belief propagation. In: International conference on principles and practice of constraint programming. Springer, pp 341\u2013350","DOI":"10.1007\/978-3-319-23219-5_24"},{"key":"3868_CR23","unstructured":"Pytorch (2016) Pytorch. \nhttps:\/\/github.com\/pytorch\/pytorch"},{"key":"3868_CR24","unstructured":"Roberts A, Engel J, Raffel C, Hawthorne C, Eck D (2018) A hierarchical latent vector model for learning long-term structure in music. ArXiv e-prints \narXiv:1803.05428"},{"issue":"1","key":"3868_CR25","doi-asserted-by":"publisher","first-page":"9172","DOI":"10.1038\/s41598-017-08028-4","volume":"7","author":"J Sakellariou","year":"2017","unstructured":"Sakellariou J, Tria F, Loreto V, Pachet F (2017) Maximum entropy models capture melodic styles. Sci Rep 7(1):9172. \nhttps:\/\/doi.org\/10.1038\/s41598-017-08028-4","journal-title":"Sci Rep"},{"issue":"11","key":"3868_CR26","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster M, Paliwal KK (1997) Bidirectional recurrent neural networks. IEEE Trans Signal Process 45(11):2673\u20132681","journal-title":"IEEE Trans Signal Process"},{"key":"3868_CR27","unstructured":"Serdyuk D, Ke NR, Sordoni A, Pal C, Bengio Y (2017) Twin networks: using the future as a regularizer. CoRR \narxiv: abs\/1708.06742"},{"key":"3868_CR28","unstructured":"Shabanian S, Arpit D, Trischler A, Bengio Y (2017) Variational Bi-LSTMs. ArXiv e-prints \narXiv:1711.05717"},{"key":"3868_CR29","unstructured":"Sturm BL, Santos JF, Ben-Tal O, Korshunova I (2016) Music transcription modelling and composition using deep learning. \nArXiv:1604.08723v1"},{"key":"3868_CR30","unstructured":"Walder C, Kim D (2016) Computer assisted composition with recurrent neural networks. arXiv preprint \narXiv:161200092"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3868-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-018-3868-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-018-3868-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,30]],"date-time":"2020-01-30T04:14:45Z","timestamp":1580357685000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-018-3868-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,20]]},"references-count":30,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["3868"],"URL":"https:\/\/doi.org\/10.1007\/s00521-018-3868-4","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2018,11,20]]},"assertion":[{"value":"17 November 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 November 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 November 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}