{"type":"ScholarlyArticle","title":"XAI-Lyricist: Improving the Singability of AI-Generated Lyrics with Prosody Explanations","authors":[{"name":"Qihao Liang","slug":"qihao-liang","given":"Qihao","family":"Liang","affiliation":"National University of Singapore"},{"name":"Xichu Ma","slug":"xichu-ma","given":"Xichu","family":"Ma","affiliation":"National University of Singapore"},{"name":"Finale Doshi-Velez","slug":"finale-doshi-velez","given":"Finale","family":"Doshi-Velez","affiliation":"Harvard University"},{"name":"Brian Lim","slug":"brian-lim","given":"Brian","family":"Lim","affiliation":"National University of Singapore"},{"name":"Ye Wang","slug":"ye-wang","given":"Ye","family":"Wang","affiliation":"National University of Singapore"}],"abstract":"Explaining the singability of lyrics is an important but missing ability of language models (LMs) in song lyrics generation. This ability allows songwriters to quickly assess if LM-generated lyrics can be sung harmoniously with melodies and helps singers align lyrics with melodies during practice. This paper presents XAI-Lyricist, leveraging musical prosody to guide LMs in generating singable lyrics and providing human-understandable singability explanations. We employ a Transformer model to generate lyrics under musical prosody constraints and provide demonstrations of the lyrics' prosody patterns as singability explanations. XAI-Lyricist is evaluated by computational metrics (perplexity, prosody-BLEU) and a human-grounded study (human ratings, average time and number of attempts for singing). Experimental results show that musical prosody can significantly improve the singability of LM-generated lyrics. A controlled study with 14 singers also confirms the usefulness of the provided explanations in helping them to interpret lyrical singability faster than reading plain text lyrics.","doi":"10.24963/ijcai.2024/872","url":"https://ijcai.org/proceedings/2024/872","pdf":"https://ijcai.org/proceedings/2024/0872.pdf","markdown":"https://ijcai.org/proceedings/2024/872.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/872","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Human-Centred AI","track":"Human-Centred AI","number":872,"pages":{"first":7877,"last":7885},"keywords":["Multidisciplinary Topics and Applications: MTA: Arts and creativity","Humans and AI: HAI: Human-AI collaboration","AI Ethics, Trust, Fairness: ETF: Explainability and interpretability"],"videos":[],"references":[{"position":1,"raw":"[Barradas and Sakka, 2022] Gonc ¸alo T Barradas and Laura S Sakka. When words matter: A cross-cultural perspective on lyrics and their relationship to musical emotions. Psychology of Music, 50(2):650-669, 2022.","title":"When words matter: A cross-cultural perspective on lyrics and their relationship to musical emotions","authors":"Sakka ; Gonc Barradas, T ¸alo, Laura S Barradas, Sakka","year":"2022","venue":"Psychology of Music","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Brattico et al., 2011] Elvira Brattico, Vinoo Alluri, Brigitte Bogert, Thomas Jacobsen, Nuutti Vartiainen, Sirke Niemi- nen, and Mari Tervaniemi. A functional mri study of happy and sad emotions in music with and without lyrics. Fron- tiers in psychology, 2:308, 2011.","title":"A functional mri study of happy and sad emotions in music with and without lyrics","authors":"Elvira Brattico, Vinoo Alluri, Brigitte Bogert, Thomas Jacobsen, Nuutti Vartiainen, Sirke Nieminen, Mari Tervaniemi","year":"2011","venue":"Frontiers in psychology","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Bryan-Kinns et al., 2023] Nick Bryan-Kinns, Berker Banar, Corey Ford, Courtney N Reed, Yixiao Zhang, Simon Colton, and Jack Armitage. Exploring xai for the arts: Ex- plaining latent space in generative music. arXiv preprint arXiv:2308.05496, 2023.","title":"Exploring xai for the arts: Explaining latent space in generative music","authors":"Nick Bryan-Kinns, Berker Banar, Corey Ford, Courtney N Reed, Yixiao Zhang, Simon Colton, Jack Armitage","year":"2023","venue":null,"doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Caccia and Lorusso, 2021] Martina Caccia and Maria Luisa Lorusso. The processing of rhythmic structures in music and prosody by children with developmental dyslexia and developmental language disorder. Developmental science, 24(1):e12981, 2021.","title":"The processing of rhythmic structures in music and prosody by children with developmental dyslexia and developmental language disorder","authors":"Lorusso Caccia, Martina Caccia, Maria Luisa, Lorusso","year":"2021","venue":"Developmental science","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Chang et al., 2021] Jia-Wei Chang, Jason C. Hung, and Kuan-Cheng Lin. Singability-enhanced lyric generator with music style transfer. Computer Communications, 168:33-53, 2021.","title":"Singability-enhanced lyric generator with music style transfer","authors":"Jia-Wei Chang, Jason C Hung, Kuan-Cheng Lin","year":"2021","venue":"Computer Communications","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Chen and Lerch, 2020] Yihao Chen and Alexander Lerch. Melody-conditioned lyrics generation with seqgans. 2020 IEEE International Symposium on Multimedia (ISM), pages 189-196, 2020.","title":"Melody-conditioned lyrics generation with seqgans","authors":"Chen, Lerch, Yihao Chen, Alexander Lerch","year":"2020","venue":"IEEE International Symposium on Multimedia (ISM)","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Chen et al., 2008] Stanley F Chen, Douglas Beeferman, and Roni Rosenfeld. Evaluation Metrics For Language Mod- els. 1 2008.","title":"Evaluation Metrics For Language Models","authors":"Douglas Stanley F Chen, Roni Beeferman, Rosenfeld","year":"2008","venue":null,"doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Everhardt et al., 2022] Marita K Everhardt, Anastasios Sarampalis, Matt Coler, Deniz Bas ¸kent, and Wander Lowie. Speech prosody: the musical, magical quality of speech. Front. Young Minds, 10(698575):10-3389, 2022.","title":"Speech prosody: the musical, magical quality of speech","authors":"Anastasios Marita K Everhardt, Matt Sarampalis, Deniz Coler, Wander Bas, Lowie","year":"2022","venue":"Front. Young Minds","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Franzon, 2008] Johan Franzon. Choices in song translation: Singability in print, subtitles and sung performance. The Translator, 14(2):373-399, 2008.","title":"Choices in song translation: Singability in print, subtitles and sung performance","authors":"Johan Franzon, Franzon","year":"2008","venue":"The Translator","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Gordon et al., 2011] Reyna L Gordon, Cyrille L Magne, and Edward W Large. Eeg correlates of song prosody: A new look at the relationship between linguistic and mu- sical rhythm. Frontiers in psychology, 2:352, 2011.","title":"Eeg correlates of song prosody: A new look at the relationship between linguistic and musical rhythm","authors":"Cyrille L Reyna L Gordon, Edward W Magne, Large","year":"2011","venue":"Frontiers in psychology","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Güven, 2019] Mine Güven. Why \"sway\" again? prosodic constraints and singability in song (re)translation. Studies from a Retranslation Culture: The Turkish Context, pages 177-194, 2019.","title":"Why \"sway\" again? prosodic constraints and singability in song (re)translation","authors":"Mine Güven, Güven","year":"2019","venue":"Studies from a Retranslation Culture: The Turkish Context","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Hansen et al., 2021] Niels Chr Hansen, Haley E Kragness, Peter Vuust, Laurel Trainor, and Marcus T Pearce. Predic- tive uncertainty underlies auditory boundary perception. Psychological science, 32(9):1416-1425, 2021.","title":"Predictive uncertainty underlies auditory boundary perception","authors":"Hansen","year":"2021","venue":"Psychological science","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Heffner and Slevc, 2015] Christopher C Heffner and L Robert Slevc. Prosodic structure as a parallel to musical structure. Frontiers in psychology, 6:1962, 2015.","title":"Prosodic structure as a parallel to musical structure","authors":"C Christopher, L Heffner, Slevc Robert","year":"2015","venue":"Frontiers in psychology","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Hsiao et al., 2021] Wen-Yi Hsiao, Jen-Yu Liu, Yin-Cheng Yeh, and Yi-Hsuan Yang. Compound word transformer: Learning to compose full-song music over dynamic di- rected hypergraphs. Proceedings of the AAAI Conference on Artificial Intelligence, 35(1):178-186, May 2021.","title":"Compound word transformer: Learning to compose full-song music over dynamic directed hypergraphs","authors":"Wen-Yi Hsiao, Jen-Yu Liu, Yin-Cheng Yeh, Yi-Hsuan Yang","year":"2021","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Jansen et al., 2023] Nelleke Jansen, Hanneke Loerts, Eleanor Harding, Deniz Baskent, and Wander Lowie. The influence of musical abilities on the processing of second language prosody: An eye-tracking study. The Journal of the Acoustical Society of America, 153(3 supplement):A157-A157, 2023.","title":"The influence of musical abilities on the processing of second language prosody: An eye-tracking study","authors":"Nelleke Jansen, Hanneke Loerts, Eleanor Harding, Deniz Baskent, Wander Lowie","year":"2023","venue":"The Journal of the Acoustical Society of America","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Jelinek et al., 2005] F. Jelinek, R. L. Mercer, L. R. Bahl, and J. K. Baker. Perplexity-a measure of the difficulty of speech recognition tasks. The Journal of the Acoustical Society of America, 62(S1):S63-S63, 08 2005.","title":"Perplexity-a measure of the difficulty of speech recognition tasks","authors":"F Jelinek, R L Mercer, L R Bahl, J K Baker","year":"2005","venue":"The Journal of the Acoustical Society of America","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Khoshsaligheh and Ameri, 2016] Masood Khoshsaligheh and Saeed Ameri. Exploring the singability of songs in a monster in paris dubbed into persian. Asia Pacific Translation and Intercultural Studies, 3(1):76-90, 2016.","title":"Exploring the singability of songs in a monster in paris dubbed into persian","authors":"Masood Khoshsaligheh, Saeed Ameri","year":"2016","venue":"Asia Pacific Translation and Intercultural Studies","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Lewis et al., 2020] Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7871-7880, Online, July 2020. Association for Computational Linguistics.","title":"BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension","authors":"Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, Luke Zettlemoyer","year":"2020","venue":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Liang and Wang, 2024] Qihao Liang and Ye Wang. Drawlody: Sketch-based melody creation with enhanced usability and interpretability. IEEE Transactions on Multimedia, 26:7074-7088, 2024.","title":"Drawlody: Sketch-based melody creation with enhanced usability and interpretability","authors":"Wang ; ] Qihao Liang, Ye Liang, Wang","year":"2024","venue":"IEEE Transactions on Multimedia","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Lloyd, 2020] Dan Lloyd. The musical structure of time in the brain: Repetition, rhythm, and harmony in fmri dur- ing rest and passive movie viewing. Frontiers in computa- tional neuroscience, 13:98, 2020.","title":"The musical structure of time in the brain: Repetition, rhythm, and harmony in fmri during rest and passive movie viewing","authors":"Dan Lloyd","year":"2020","venue":"Frontiers in computational neuroscience","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Ma et al., 2021] Xichu Ma, Ye Wang, Min-Yen Kan, and Wee Sun Lee. Ai-lyricist: Generating music and vocabu- lary constrained lyrics. In Proceedings of the 29th ACM In- ternational Conference on Multimedia, pages 1002-1011, 2021.","title":"Ai-lyricist: Generating music and vocabulary constrained lyrics","authors":"Ma","year":"2021","venue":"Proceedings of the 29th ACM International Conference on Multimedia","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Malmi et al., 2016] Eric Malmi, Pyry Takala, Hannu Toivo- nen, Tapani Raiko, and Aristides Gionis. Dopelearning: A computational approach to rap lyrics generation. In Pro- ceedings of the 22nd ACM SIGKDD International Con- ference on Knowledge Discovery and Data Mining, pages 195-204, 2016.","title":"Dopelearning: A computational approach to rap lyrics generation","authors":"Eric Malmi, Pyry Takala, Hannu Toivonen, Tapani Raiko, Aristides Gionis","year":"2016","venue":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Nichols et al., 2009] Eric Nichols, Dan Morris, Sumit Basu, and Christopher Raphael. Relationships between lyrics and melody in popular music. In ISMIR 2009-Proceedings of the 11th International Society for Music Information Retrieval Conference, pages 471-476, 2009.","title":"Relationships between lyrics and melody in popular music","authors":"Eric Nichols, Dan Morris, Sumit Basu, Christopher Raphael","year":"2009","venue":"ISMIR 2009-Proceedings of the 11th International Society for Music Information Retrieval Conference","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Palmer and Hutchins, 2006] Caroline Palmer and Sean Hutchins. What is musical prosody? Psychology of learn- ing and motivation, 46:245-278, 2006.","title":"What is musical prosody?","authors":"Hutchins Palmer, Caroline Palmer, Sean Hutchins","year":"2006","venue":"Psychology of learning and motivation","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Palmer and Kelly, 1992] Caroline Palmer and Michael H Kelly. Linguistic prosody and musical meter in song. Jour- nal of memory and language, 31(4):525-542, 1992.","title":"Linguistic prosody and musical meter in song","authors":"Caroline Palmer, Michael H Kelly","year":"1992","venue":"Journal of memory and language","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Papineni et al., 2002] Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. Bleu: a method for au- tomatic evaluation of machine translation. In Proceedings of the 40th Annual Meeting of the Association for Compu- tational Linguistics, pages 311-318, Philadelphia, Penn- sylvania, USA, July 2002. Association for Computational Linguistics.","title":"Bleu: a method for automatic evaluation of machine translation","authors":"Kishore Papineni, Salim Roukos, Todd Ward, Wei-Jing Zhu","year":"2002","venue":"Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Patel and Iversen, 2007] Aniruddh D Patel and John R Iversen. The linguistic benefits of musical abilities. Trends in cognitive sciences, 11(9):369-372, 2007.","title":"The linguistic benefits of musical abilities","authors":"D Aniruddh, John R Patel, Iversen","year":"2007","venue":"Trends in cognitive sciences","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Potash et al., 2015] Peter Potash, Alexey Romanov, and Anna Rumshisky. Ghostwriter: Using an lstm for auto- matic rap lyric generation. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pages 1919-1924, 2015.","title":"Ghostwriter: Using an lstm for automatic rap lyric generation","authors":"Potash","year":"2015","venue":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Sahasrabuddhe, 2023] Hari Sahasrabuddhe. Role of prosody in music meaning. In Computer Assisted Music and Dramatics: Possibilities and Challenges, pages 71- 76. Springer, 2023.","title":"Role of prosody in music meaning","authors":"Hari Sahasrabuddhe, Sahasrabuddhe","year":"2023","venue":"Computer Assisted Music and Dramatics: Possibilities and Challenges","doi":null,"url":null,"internal_url":null},{"position":30,"raw":"[Sheng et al., 2021] Zhonghao Sheng, Kaitao Song, Xu Tan, Yi Ren, Wei Ye, Shikun Zhang, and Tao Qin. Songmass: Automatic song writing with pre-training and alignment constraint. Proceedings of the AAAI Conference on Artifi- cial Intelligence, 35(15):13798-13805, May 2021.","title":"Songmass: Automatic song writing with pre-training and alignment constraint","authors":"Zhonghao Sheng, Kaitao Song, Xu Tan, Yi Ren, Wei Ye, Shikun Zhang, Tao Qin","year":"2021","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":31,"raw":"[Sogunro, 2022] Bolanle O Sogunro. Phonological and soci- olinguistic challenges of translating yorùbá play, and game songs to singable english for children. Yoruba Studies Re- view, 7(1):1-14, 2022.","title":"Phonological and sociolinguistic challenges of translating yorùbá play, and game songs to singable english for children","authors":"O Bolanle, Sogunro","year":"2022","venue":"Yoruba Studies Review","doi":null,"url":null,"internal_url":null},{"position":32,"raw":"[Tian et al., 2023] Yufei Tian, Anjali Narayan-Chen, Shereen Oraby, Alessandra Cervone, Gunnar Sigurdsson, Chenyang Tao, Wenbo Zhao, Tagyoung Chung, Jing Huang, and Nanyun Peng. Unsupervised melody-to-lyrics generation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 9235-9254, Toronto, Canada, July 2023. Association for Computational Linguistics.","title":"Unsupervised melody-to-lyrics generation","authors":"Yufei Tian, Anjali Narayan-Chen, Shereen Oraby, Alessandra Cervone, Gunnar Sigurdsson, Chenyang Tao, Wenbo Zhao, Tagyoung Chung, Jing Huang, Nanyun Peng","year":"2023","venue":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics","doi":null,"url":null,"internal_url":null},{"position":33,"raw":"[Vaswani et al., 2017] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. Attention is all you need. In Advances in Neural Information Processing Sys- tems, volume 30.","title":"Attention is all you need","authors":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł Ukasz Kaiser, Illia Polosukhin","year":null,"venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":34,"raw":"Curran Associates, Inc., 2017.","title":null,"authors":"Curran Associates, Inc","year":"2017","venue":null,"doi":null,"url":null,"internal_url":null},{"position":35,"raw":"[Wang et al., 2020] Ziyu Wang, Dingsu Wang, Yixiao Zhang, and Gus Xia. Learning interpretable representa- tion for controllable polyphonic music generation. In Pro- ceedings of the 21th International Society for Music In- formation Retrieval Conference, ISMIR 2020, Montreal, Canada, October 11-16, 2020, pages 662-669, 2020.","title":"Learning interpretable representation for controllable polyphonic music generation","authors":"Ziyu Wang, Dingsu Wang, Yixiao Zhang, Gus Xia","year":"2020","venue":"Pro-ceedings of the 21th International Society for Music Information Retrieval Conference, ISMIR 2020","doi":null,"url":null,"internal_url":null},{"position":36,"raw":"[Wang et al., 2022] Zihao Wang, Kejun Zhang, Yuxing Wang, Chen Zhang, Qihao Liang, Pengfei Yu, Yongsheng Feng, Wenbo Liu, Yikai Wang, Yuntao Bao, et al. Song- driver: Real-time music accompaniment generation with- out logical latency nor exposure bias. In Proceedings of the 30th ACM International Conference on Multimedia, pages 1057-1067, 2022.","title":"Songdriver: Real-time music accompaniment generation without logical latency nor exposure bias","authors":"Zihao Wang, Kejun Zhang, Yuxing Wang, Chen Zhang, Qihao Liang, Pengfei Yu, Yongsheng Feng, Wenbo Liu, Yikai Wang, Yuntao Bao","year":"2022","venue":"Proceedings of the 30th ACM International Conference on Multimedia","doi":null,"url":null,"internal_url":null},{"position":37,"raw":"[Watanabe et al., 2014] Kento Watanabe, Yuichiroh Matsub- ayashi, Kentaro Inui, and Masataka Goto. Modeling struc- tural topic transitions for automatic lyrics generation. In Proceedings of the 28th Pacific Asia conference on lan- guage, information and computing, pages 422-431, 2014.","title":"Modeling structural topic transitions for automatic lyrics generation","authors":"Kento Watanabe, Yuichiroh Matsubayashi, Kentaro Inui, Masataka Goto","year":"2014","venue":"Proceedings of the 28th Pacific Asia conference on language, information and computing","doi":null,"url":null,"internal_url":null},{"position":38,"raw":"[Watanabe et al., 2018] Kento Watanabe, Yuichiroh Matsub- ayashi, Satoru Fukayama, Masataka Goto, Kentaro Inui, and Tomoyasu Nakano. A melody-conditioned lyrics lan- guage model. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Com- putational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 163-172, New Orleans, Louisiana, June 2018. Association for Computational Lin- guistics.","title":"A melody-conditioned lyrics language model","authors":"Kento Watanabe, Yuichiroh Matsubayashi, Satoru Fukayama, Masataka Goto, Kentaro Inui, Tomoyasu Nakano","year":"2018","venue":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","doi":null,"url":null,"internal_url":null},{"position":39,"raw":"[Wu et al., 2019] Xing Wu, Zhikang Du, Yike Guo, and Hamido Fujita. Hierarchical attention based long short- term memory for chinese lyric generation. Applied Intelli- gence, 49:44-52, 2019.","title":"Hierarchical attention based long shortterm memory for chinese lyric generation","authors":"Xing Wu, Zhikang Du, Yike Guo, Hamido Fujita","year":"2019","venue":"Applied Intelligence","doi":null,"url":null,"internal_url":null},{"position":40,"raw":"[Yan et al., 2023] Zihan Yan, Chunxu Yang, Qihao Liang, and Xiang 'Anthony' Chen. Xcreation: A graph-based crossmodal generative creativity support tool. In Proceed- ings of the 36th Annual ACM Symposium on User Inter- face Software and Technology, UIST '23, New York, NY, USA, 2023. Association for Computing Machinery.","title":"Xcreation: A graph-based crossmodal generative creativity support tool","authors":"Zihan Yan, Chunxu Yang, Qihao Liang, Xiang ' Anthony' Chen","year":"2023","venue":"Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, UIST '23","doi":null,"url":null,"internal_url":null},{"position":41,"raw":"[Zhang et al., 2020] Rongsheng Zhang, Xiaoxi Mao, Le Li, Lin Jiang, Lin Chen, Zhiwei Hu, Yadong Xi, Changjie Fan, and Minlie Huang. Youling: an AI-assisted lyrics creation system. In Proceedings of the 2020 Conference on Em- pirical Methods in Natural Language Processing: System Demonstrations, pages 85-91, Online, October 2020. As- sociation for Computational Linguistics.","title":"Youling: an AI-assisted lyrics creation system","authors":"Zhang","year":"2020","venue":"Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations","doi":null,"url":null,"internal_url":null},{"position":42,"raw":"[Zhang et al., 2023] Kejun Zhang, Xinda Wu, Tieyao Zhang, Zhijie Huang, Xu Tan, Qihao Liang, Songruoyao Wu, and Lingyun Sun. Wuyun: exploring hierarchical skeleton- guided melody generation using knowledge-enhanced deep learning. arXiv preprint arXiv:2301.04488, 2023.","title":"Wuyun: exploring hierarchical skeletonguided melody generation using knowledge-enhanced deep learning","authors":"Kejun Zhang, Xinda Wu, Tieyao Zhang, Zhijie Huang, Xu Tan, Qihao Liang, Songruoyao Wu, Lingyun Sun","year":"2023","venue":null,"doi":null,"url":null,"internal_url":null},{"position":43,"raw":"[Zhao et al., 2019] Guoshuai Zhao, Hao Fu, Ruihua Song, Tetsuya Sakai, Zhongxia Chen, Xing Xie, and Xueming Qian. Personalized reason generation for explainable song recommendation. ACM Transactions on Intelligent Sys- tems and Technology (TIST), 10(4):1-21, 2019.","title":"Personalized reason generation for explainable song recommendation","authors":"Guoshuai Zhao, Hao Fu, Ruihua Song, Tetsuya Sakai, Zhongxia Chen, Xing Xie, Xueming Qian","year":"2019","venue":"ACM Transactions on Intelligent Systems and Technology (TIST)","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}