{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:03:17Z","timestamp":1743109397614,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":13,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811561672"},{"type":"electronic","value":"9789811561689"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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\/978-981-15-6168-9_26","type":"book-chapter","created":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T12:39:31Z","timestamp":1593607171000},"page":"307-318","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Rap Lyrics Generation Using Vowel GAN"],"prefix":"10.1007","author":[{"given":"Tomoya","family":"Miyano","sequence":"first","affiliation":[]},{"given":"Hiroaki","family":"Saito","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,7,2]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Ghazvininejad, M., Shi, X., Choi, Y., Knight, K.: Generating topical poetry. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pp. 1183\u20131191 (2016)","key":"26_CR1","DOI":"10.18653\/v1\/D16-1126"},{"doi-asserted-by":"crossref","unstructured":"Lau, H.J., Cohn, T., Baldwin, T., Brooke, J., Hammond, A.: Deep-speare: a joint neural model of poetic language, meter and rhyme. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018) (2018)","key":"26_CR2","DOI":"10.18653\/v1\/P18-1181"},{"unstructured":"Gerv\u00e1s, P.: WASP: evaluation of different strategies for the automatic generation of Spanish verse. In: Proceedings of the AISB 2000 Symposium on Creative & Cultural Aspects of AI, pp. 93\u2013100 (2000)","key":"26_CR3"},{"unstructured":"Oliveira, H.: Automatic generation of poetry: an overview. In: Proceedings of 1st Seminar of Art, Music, Creativity and Artificial Intelligence (2009)","key":"26_CR4"},{"unstructured":"Oliveira, H.: PoeTryMe: a versatile platform for poetry generation. In: Computational Creativity, Concept Invention, and General Intelligence, vol. 1 (2012)","key":"26_CR5"},{"unstructured":"Agirrezabal, M., Arrieta, B., Astigarraga, A., Hulden, M.: POS-tag based poetry generation with WordNet. In: Proceedings of the 14th European Workshop on Natural Language Generation, pp. 162\u2013166 (2013)","key":"26_CR6"},{"unstructured":"Greene, E., Bodrumlu, T., Knight, K.: Automatic analysis of rhythmic poetry with applications to generation and translation. In: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp. 524\u2013533 (2010)","key":"26_CR7"},{"unstructured":"Yan, R.: i, Poet: automatic poetry composition through recurrent neural networks with iterative polishing schema. In: IJCAI, pp. 2238\u20132244 (2016)","key":"26_CR8"},{"doi-asserted-by":"crossref","unstructured":"Yu, L., Zhang, W., Wang, J., Yu, Y.: SeqGAN: sequence generative adversarial nets with policy gradient. In: 31st AAAI Conference on Artificial Intelligence (2017)","key":"26_CR9","DOI":"10.1609\/aaai.v31i1.10804"},{"unstructured":"Zhou, M., Jiang, L., He, J.: Generating Chinese couplets and quatrain using a statistical approach. In: Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation, vol. 1 (2009)","key":"26_CR10"},{"key":"26_CR11","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/978-3-319-69005-6_18","volume-title":"Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data","author":"X Yi","year":"2017","unstructured":"Yi, X., Li, R., Sun, M.: Generating Chinese classical poems with RNN encoder-decoder. In: Sun, M., Wang, X., Chang, B., Xiong, D. (eds.) CCL\/NLP-NABD -2017. LNCS (LNAI), vol. 10565, pp. 211\u2013223. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-69005-6_18"},{"doi-asserted-by":"crossref","unstructured":"Malmi, E., Takala, P., Toivonen, H., Raiko, T., Gionis, A.: DopeLearning: a computational approach to rap lyrics generation. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 195\u2013204. ACM (2016)","key":"26_CR12","DOI":"10.1145\/2939672.2939679"},{"unstructured":"Wu. D., Addanki, K.: Learning to rap battle with bilingual recursive neural networks. In: 24th International Joint Conference on Artificial Intelligence (2015)","key":"26_CR13"}],"container-title":["Communications in Computer and Information Science","Computational Linguistics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-6168-9_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T15:38:00Z","timestamp":1667230680000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-6168-9_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9789811561672","9789811561689"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-6168-9_26","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"2 July 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PACLING","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference of the Pacific Association for Computational Linguistics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hanoi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpacl2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pacling2019.fpt.edu.vn","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":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"70","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":"28","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":"14","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":"40% - 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)"}}]}}