{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T20:59:40Z","timestamp":1764277180914,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031299551"},{"type":"electronic","value":"9783031299568"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-29956-8_1","type":"book-chapter","created":{"date-parts":[[2023,4,4]],"date-time":"2023-04-04T23:03:58Z","timestamp":1680649438000},"page":"3-19","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["LooperGP: A Loopable Sequence Model for\u00a0Live Coding Performance Using GuitarPro Tablature"],"prefix":"10.1007","author":[{"given":"Sara","family":"Adkins","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4518-0194","authenticated-orcid":false,"given":"Pedro","family":"Sarmento","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9869-1668","authenticated-orcid":false,"given":"Mathieu","family":"Barthet","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,1]]},"reference":[{"key":"1_CR1","unstructured":"Statsmodels (2022). https:\/\/github.com\/statsmodels\/statsmodels. Accessed 14 Aug 2022"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Ackley, D.H., Hinton, G.E., Sejnowski, T.J.: A learning algorithm for Boltzmann machines. Cognit. Sci. 147\u2013169 (1985)","DOI":"10.1016\/S0364-0213(85)80012-4"},{"key":"1_CR3","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1162\/comj.2009.33.2.48","volume":"33","author":"C Ariza","year":"2009","unstructured":"Ariza, C.: The interrogator as critic: the turing test and the evaluation of generative music. Comput. Music. J. 33, 48\u201370 (2009)","journal-title":"Comput. Music. J."},{"key":"1_CR4","doi-asserted-by":"crossref","first-page":"297","DOI":"10.70252\/LANZ1453","volume":"8","author":"PA Bishop","year":"2015","unstructured":"Bishop, P.A., Herron, R.L.: Use and misuse of the likert item responses and other ordinal measures. Int. J. Exer. Sci. 8, 297\u2013302 (2015)","journal-title":"Int. J. Exer. Sci."},{"key":"1_CR5","doi-asserted-by":"publisher","unstructured":"Briot, J.P., Hadjeres, G., Pachet, F.D.: Deep Learning Techniques for Music Generation, vol. 1. Springer, Cham (2020). doi: https:\/\/doi.org\/10.1007\/978-3-319-70163-9","DOI":"10.1007\/978-3-319-70163-9"},{"key":"1_CR6","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1080\/07494460802663991","volume":"28","author":"AR Brown","year":"2009","unstructured":"Brown, A.R., Sorensen, A.: Interacting with generative music through live coding. Contemp. Music. Rev. 28, 17\u201329 (2009)","journal-title":"Contemp. Music. Rev."},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Chandna, P., Ramires, A., Serra, X., G\u00f3mez, E.: Loopnet: Musical loop synthesis conditioned on intuitive musical parameters. In: ICASSP 2021\u20132021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3395\u20133399. IEEE (2021)","DOI":"10.1109\/ICASSP39728.2021.9415047"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"Dai, Z., Yang, Z., Yang, Y., Carbonell, J., Le, Q.V., Salakhutdinov, R.: Transformer-xl: Attentive language models beyond a fixed-length context. arXiv preprint arXiv:1901.02860 (2019)","DOI":"10.18653\/v1\/P19-1285"},{"key":"1_CR9","unstructured":"Hadjeres, G., Pachet, F., Nielsen, F.: Deepbach: a steerable model for bach chorales generation. In: International Conference on Machine Learning, pp. 1362\u20131371 (2017)"},{"key":"1_CR10","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1109\/6046.944475","volume":"3","author":"JL Hsu","year":"2001","unstructured":"Hsu, J.L., Liu, C.C., Chen, A.L.: Discovering nontrivial repeating patterns in music data. IEEE Trans. Multimedia 3, 311\u2013325 (2001)","journal-title":"IEEE Trans. Multimedia"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Huang, Y.S., Yang, Y.H.: Pop music transformer: beat-based modeling and generation of expressive pop piano compositions. In: Proceedings of the 28th ACM International Conference on Multimedia, pp. 1180\u20131188 (2020)","DOI":"10.1145\/3394171.3413671"},{"key":"1_CR12","unstructured":"Ji, S., Luo, J., Yang, X.: A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions. arXiv preprint arXiv:2011.06801 (2020)"},{"key":"1_CR13","unstructured":"Lan, Q., T\u00f8rresen, J., Jensenius, A.R.: Raveforce: a deep reinforcement learning environment for music. In: Proceedings of the SMC conferences, pp. 217\u2013222. Society for Sound and Music Computing (2019)"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Magnusson, T.: Sonic Writing: Technologies of Material, Symbolic, and Signal Inscriptions. Bloomsbury Publishing USA (2019)","DOI":"10.5040\/9781501313899"},{"key":"1_CR15","unstructured":"McCartney, J.: Supercollider: A new real-time sound synthesis language. In: Proceedings of the International Computer Music Conference, pp. 257\u2013258 (1996)"},{"key":"1_CR16","unstructured":"McLean, A., Wiggins, G.: Tidal-pattern language for the live coding of music. In: Proceedings of the 7th Sound and Music Computing Conference, pp. 331\u2013334 (2010)"},{"key":"1_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.jml.2020.104092","volume":"112","author":"L Meteyard","year":"2020","unstructured":"Meteyard, L., Davies, R.A.: Best practice guidance for linear mixed-effects models in psychological science. J. Mem. Lang. 112, 104092 (2020)","journal-title":"J. Mem. Lang."},{"key":"1_CR18","unstructured":"Mueller, A.: Word cloud (2022). https:\/\/github.com\/amueller\/word_cloud. Accessed: 14 Aug 2022"},{"issue":"2","key":"1_CR19","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0089642","volume":"9","author":"D M\u00fcllensiefen","year":"2014","unstructured":"M\u00fcllensiefen, D., Gingras, B., Musil, J., Stewart, L.: The musicality of non-musicians: an index for assessing musical sophistication in the general population. PLoS ONE 9(2), e89642 (2014)","journal-title":"PLoS ONE"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Nilson, C.: Live coding practice. In: Proceedings of the 7th International Conference on New Interfaces for Musical Expression, pp. 112\u2013117 (2007)","DOI":"10.1145\/1279740.1279760"},{"key":"1_CR21","unstructured":"Ramires, A., et al.: The freesound loop dataset and annotation tool. arXiv preprint arXiv:2008.11507 (2020)"},{"key":"1_CR22","unstructured":"Sarmento, P., Kumar, A., Carr, C., Zukowski, Z., Barthet, M., Yang, Y.H.: DadaGP: a dataset of tokenized GuitarPro songs for sequence models. In: Proceedings of the 22nd International Social for Music Information Retrieval Conference (2021)"},{"key":"1_CR23","doi-asserted-by":"crossref","unstructured":"Shih, Y.J., Wu, S.L., Zalkow, F., Muller, M., Yang, Y.H.: Theme transformer: symbolic music generation with theme-conditioned transformer. IEEE Trans. Multimedia 1\u20131 (2022)","DOI":"10.1109\/TMM.2022.3161851"},{"key":"1_CR24","unstructured":"Stewart, J., Lawson, S.: CIBO: an autonomous tidalcyles performer. In: Proceedings of the Fourth International Conference on Live Coding, p. 353 (2019)"},{"key":"1_CR25","doi-asserted-by":"publisher","first-page":"541","DOI":"10.4300\/JGME-5-4-18","volume":"5","author":"GM Sullivan","year":"2013","unstructured":"Sullivan, G.M., Artino, A.R.: Analyzing and interpreting data from likert-type scales. J. Graduate Med. Educ. 5, 541\u2013542 (2013)","journal-title":"J. Graduate Med. Educ."},{"key":"1_CR26","first-page":"2851","volume":"1","author":"CH Wu","year":"2007","unstructured":"Wu, C.H.: An empirical study on the transformation of likert-scale data to numerical scores. Appl. Math. Sci. 1, 2851\u20132862 (2007)","journal-title":"Appl. Math. Sci."}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Music, Sound, Art and Design"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-29956-8_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T18:33:28Z","timestamp":1729190008000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-29956-8_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031299551","9783031299568"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-29956-8_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"1 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EvoMUSART","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Intelligence in Music, Sound, Art and Design (Part of EvoStar)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brno","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Czech Republic","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 April 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evomusart2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.evostar.org\/2023\/evomusart\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"55","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}