{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T03:18:46Z","timestamp":1743045526735,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031475450"},{"type":"electronic","value":"9783031475467"}],"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\/978-3-031-47546-7_19","type":"book-chapter","created":{"date-parts":[[2023,11,2]],"date-time":"2023-11-02T00:03:15Z","timestamp":1698883395000},"page":"278-291","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PAUL-2: An Upgraded Transformer-Based Redesign of\u00a0the\u00a0Algorithmic Composer PAUL"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0616-3081","authenticated-orcid":false,"given":"Felix","family":"Sch\u00f6n","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5673-2460","authenticated-orcid":false,"given":"Hans","family":"Tompits","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,2]]},"reference":[{"key":"19_CR1","volume-title":"Harmony & Voice Leading","author":"E Aldwell","year":"2019","unstructured":"Aldwell, E., Schachter, C., Cadwallader, A.: Harmony & Voice Leading, 5th edn. Cengage, Boston (2019)","edition":"5"},{"key":"19_CR2","unstructured":"Ba, L.J., Kiros, J.R., Hinton, G.E.: Layer normalization. arXiv:1607.06450 (2016)"},{"issue":"2","key":"19_CR3","first-page":"99","volume":"27","author":"C Bell","year":"2011","unstructured":"Bell, C.: Algorithmic music composition using dynamic Markov chains and genetic algorithms. J. Comput. Sci. Coll. 27(2), 99\u2013107 (2011)","journal-title":"J. Comput. Sci. Coll."},{"key":"19_CR4","volume-title":"Music in Theory and Practice: Volume 1","author":"B Benward","year":"2009","unstructured":"Benward, B., Saker, M.: Music in Theory and Practice: Volume 1, 8th edn. McGraw-Hill, New York (2009)","edition":"8"},{"key":"19_CR5","unstructured":"Biles, J.A.: Autonomous GenJam: eliminating the fitness bottleneck by eliminating fitness. In: Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation (GECCO 2001) (2001)"},{"key":"19_CR6","unstructured":"Dhariwal, P., Jun, H., Payne, C., Kim, J.W., Radford, A., Sutskever, I.: Jukebox: a generative model for music. arXiv:2005.00341 (2020)"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Eck, D., Schmidhuber, J.: Finding temporal structure in music: blues improvisation with LSTM recurrent networks. In: Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing (NNSP 2002), pp. 747\u2013756. IEEE (2002)","DOI":"10.1109\/NNSP.2002.1030094"},{"key":"19_CR8","unstructured":"Eigenfeldt, A., Pasquier, P.: Realtime generation of harmonic progressions using constrained Markov selection. In: Proceedings of the 1st International Conference on Computational Creativity (ICCC 2010), pp. 16\u201325. Computationalcreativity.net (2010)"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Ferreira, L.N., Lelis, L.H.S., Whitehead, J.: Computer-generated music for tabletop role-playing games. In: Proceedings of the 16th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2020), pp. 59\u201365. AAAI Press (2020)","DOI":"10.1609\/aiide.v16i1.7408"},{"key":"19_CR10","unstructured":"Hamanaka, M., Hirata, K., Tojo, S.: FATTA: full automatic time-span tree analyzer. In: Proceedings of the 33rd International Computer Music Conference (ICMC 2007). Michigan Publishing (2007)"},{"issue":"8","key":"19_CR11","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.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"19_CR12","unstructured":"Huang, C.A., et al.: Music transformer: generating music with long-term structure. In: Proceedings of the 7th International Conference on Learning Representations (ICLR 2019). OpenReview.net (2019)"},{"key":"19_CR13","unstructured":"Kirke, A., Miranda, E.R.: Emergent construction of melodic pitch and hierarchy through agents communicating emotion without melodic intelligence. In: Proceedings of the 37th International Computer Music Conference (ICMC 2011). Michigan Publishing (2011)"},{"issue":"2","key":"19_CR14","doi-asserted-by":"publisher","first-page":"16","DOI":"10.18564\/jasss.2679","volume":"18","author":"A Kirke","year":"2015","unstructured":"Kirke, A., Miranda, E.R.: A multi-agent emotional society whose melodies represent its emergent social hierarchy and are generated by agent communications. J. Artif. Soc. Soc. Simul. 18(2), 16 (2015)","journal-title":"J. Artif. Soc. Soc. Simul."},{"key":"19_CR15","unstructured":"Kitani, K.M., Koike, H.: ImprovGenerator: online grammatical induction for on-the-fly improvisation accompaniment. In: Proceedings of the 10th International Conference on New Interfaces for Musical Expression (NIME 2010), pp. 469\u2013472. Nime.org (2010)"},{"key":"19_CR16","volume-title":"The Complete Musician: An Integrated Approach To Tonal Theory, Analysis, and Listening","author":"SG Laitz","year":"2012","unstructured":"Laitz, S.G.: The Complete Musician: An Integrated Approach To Tonal Theory, Analysis, and Listening, 3rd edn. Oxford University Press, Oxford (2012)","edition":"3"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Libovick\u00fd, J., Helcl, J., Marecek, D.: Input combination strategies for multi-source transformer decoder. In: Proceedings of the 3rd Conference on Machine Translation (WMT 2018), pp. 253\u2013260. Association for Computational Linguistics (2018)","DOI":"10.18653\/v1\/W18-6326"},{"key":"19_CR18","unstructured":"MIDI Manufacturers Association: The Complete MIDI 1.0 Detailed Specification (1996). https:\/\/midi.org\/"},{"key":"19_CR19","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1007\/978-1-84628-600-1_8","volume-title":"Evolutionary Computer Music","author":"ER Miranda","year":"2007","unstructured":"Miranda, E.R.: Cellular automata music: from sound synthesis to musical forms. In: Miranda, E.R., Biles, J.A. (eds.) Evolutionary Computer Music, pp. 170\u2013193. Springer, London (2007). https:\/\/doi.org\/10.1007\/978-1-84628-600-1_8"},{"key":"19_CR20","unstructured":"Opolka, S., Obermeier, P., Schaub, T.: Automatic genre-dependent composition using answer set programming. In: Proceedings of the 21st International Symposium on Electronic Art (ISEA 2015), pp. 627\u2013632. ISEA International, Brighton (2015)"},{"key":"19_CR21","unstructured":"Payne, C.: MuseNet (2019). https:\/\/openai.com\/research\/musenet. Accessed 20 June 2023"},{"key":"19_CR22","unstructured":"Sch\u00f6n, F.: PAUL: an algorithmic composer of two-track piano pieces using recurrent neural networks. Bachelor\u2019s thesis, Technische Universit\u00e4t Wien, Institute of Logic and Computation, E192-03 (2020)"},{"key":"19_CR23","unstructured":"Sch\u00f6n, F.: PAUL-2: a transformer-based algorithmic composer of two-track piano pieces. Diploma thesis, Technische Universit\u00e4t Wien, Institute of Logic and Computation, E192-03 (2023)"},{"key":"19_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1007\/978-3-031-16474-3_34","volume-title":"Progress in Artificial Intelligence","author":"F Sch\u00f6n","year":"2022","unstructured":"Sch\u00f6n, F., Tompits, H.: PAUL: an algorithmic composer for classical piano music supporting multiple complexity levels. In: Marreiros, G., Martins, B., Paiva, A., Ribeiro, B., Sardinha, A. (eds.) EPIA 2022. LNCS, vol. 13566, pp. 415\u2013426. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16474-3_34"},{"key":"19_CR25","unstructured":"Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks. In: Proceedings of the 27th Annual Conference on Neural Information Processing Systems (NIPS 2014), pp. 3104\u20133112 (2014)"},{"key":"19_CR26","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Proceedings of the 30th Annual Conference on Neural Information Processing Systems (NIPS 2017), pp. 5998\u20136008 (2017)"}],"container-title":["Lecture Notes in Computer Science","AIxIA 2023 \u2013 Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-47546-7_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T06:37:58Z","timestamp":1730443078000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-47546-7_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031475450","9783031475467"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-47546-7_19","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":"2 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIxIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference of the Italian Association for Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rome","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"6 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aiia2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.aixia2023.cnr.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"53","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":"33","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":"0","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":"62% - 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)"}},{"value":"20 external reviewers.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}