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Journal of Artificial General Intelligence

The Journal of the Artificial General Intelligence Society

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1946-0163
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Tra-la-Lyrics 2.0: Automatic Generation of Song Lyrics on a Semantic Domain

Hugo Gonçalo Oliveira
Published Online: 2015-12-30 | DOI: https://doi.org/10.1515/jagi-2015-0005

Abstract

Tra-la-Lyrics is a system that generates song lyrics automatically. In its original version, the main focus was to produce text where stresses matched the rhythm of given melodies. There were no concerns on whether the text made sense or if the selected words shared some kind of semantic association. In this article, we describe the development of a new version of Tra-la-Lyrics, where text is generated on a semantic domain, defined by one or more seed words. This effort involved the integration of the original rhythm module of Tra-la-Lyrics in PoeTryMe, a generic platform that generates poetry with semantically coherent sentences. To measure our progress, the rhythm, the rhymes, and the semantic coherence in lyrics produced by the original Tra-la-Lyrics were analysed and compared with lyrics produced by the new instantiation of this system, dubbed Tra-la-Lyrics 2.0. The analysis showed that, in the lyrics by the new system, words have higher semantic association among them and with the given seeds, while the rhythm is still matched and rhymes are present. The previous analysis was complemented with a crowdsourced evaluation, where contributors answered a survey about relevant features of lyrics produced by the previous and the current versions of Tra-la-Lyrics. Though tight, the survey results confirmed the improvements of the lyrics by Tra-la-Lyrics 2.0.

Keywords: computational creativity; linguistic creativity; song lyrics; poetry; rhythm; semantics

References

  • Abe, C., and Ito, A. 2012. A Japanese Lyrics Writing Support System for Amateur Songwriters. In Proceedings of 4th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2012.Google Scholar

  • Agirre, E., and Soroa, A. 2009. Personalizing PageRank for word sense disambiguation. In Proceedings of 12th Conference of the European Chapter of the Association for Computational Linguistics, EACL’09, 33–41. Athens, Greece: ACL Press.Google Scholar

  • Agirrezabal, M.; Arrieta, B.; Astigarraga, A.; and Hulden, M. 2013. POS-Tag Based Poetry Generation with WordNet. In Proceedings of the 14th European Workshop on Natural Language Generation, 162–166. Sofia, Bulgaria: ACL Press.Google Scholar

  • Barbieri, G.; Pachet, F.; Roy, P.; and Esposti, M. D. 2012. Markov Constraints for Generating Lyrics with Style. In Proceedings of 20th European Conference on Artificial Intelligence, ECAI 2012, 115–120. Montpellier, France: IOS Press.Google Scholar

  • Binsted, K., and Ritchie, G. 1994. An Implemented Model of Punning Riddles. In Procs. of 12th National Conf. on Artificial Intelligence (Vol. 1), AAAI ’94, 633–638. Menlo Park, CA, USA: AAAI Press.Google Scholar

  • Chrismartin, B.; Tobing, L.; and Manurung, R. 2015. A chart generation system for topical metrical poetry. In Proceedings of the 6th International Conference on Computational Creativity, Park City, Utah, USA, ICCC 2015.Google Scholar

  • Colton, S., and Wiggins, G. A. 2012. Computational Creativity: The Final Frontier? In Proceedings of 20th European Conference on Artificial Intelligence (ECAI 2012), volume 242 of Frontiers in Artificial Intelligence and Applications, 21–26. Montpellier, France: IOS Press.Google Scholar

  • Colton, S.; Goodwin, J.; and Veale, T. 2012. Full FACE poetry generation. In Proceedings of 3rd International Conference on Computational Creativity, Dublin, Ireland, ICCC 2012, 95–102.Google Scholar

  • Gervás, P. 2001. An expert system for the composition of formal Spanish poetry. Journal of Knowledge-Based Systems 14:200–1.Google Scholar

  • Gervás, P.; Díaz-Agudo, B.; Peinado, F.; and Hervás, R. 2005. Story plot generation based on CBR. Knowledge-Based Systems 18(4):235–242.Google Scholar

  • Gonçalo Oliveira, H., and Cardoso, A. 2014. Using a generic poetry generation system to produce song lyrics with sentiment. In Proceedings of 3rd Workshop on Computational Creativity, Concept Invention, and General Intelligence (C3GI@ECAI 2014), volume 01-2014 of Publications of the Institute of Cognitive Science, Osnabrück. Prague, Czech Republic: Institute of Cognitive Science.Google Scholar

  • Gonçalo Oliveira, H.; Antón Pérez, L.; Costa, H.; and Gomes, P. 2011. Uma rede léxico-semântica de grandes dimensôes para o português, extraída a partir de dicionários electrónicos. Linguamática 3(2):23–38.Google Scholar

  • Gonçalo Oliveira, H.; Hervás, R.; Díaz, A.; and Gervás, P. 2014. Adapting a Generic Platform for Poetry Generation to Produce Spanish Poems. In Proceedings of 5th International Conference on Computational Creativity, Ljubljana, Slovenia, ICCC 2014.Google Scholar

  • Gonçalo Oliveira, H. R.; Cardoso, F. A.; and Pereira, F. C. 2007a. Exploring different strategies for the automatic generation of song lyrics with Tra-la-Lyrics. In Proceedings of the 13th Portuguese Conference on Artificial Intelligence, EPIA 2007, 57–68. Guimarães, Portugal: APPIA.Google Scholar

  • Gonçalo Oliveira, H. R.; Cardoso, F. A.; and Pereira, F. C. 2007b. Tra-la-Lyrics: an approach to generate text based on rhythm. In Proceedings of 4th International Joint Workshop on Computational Creativity, 47–55. London, UK: IJWCC 2007.Google Scholar

  • Gonçalo Oliveira, H. R. 2007. Geração de texto com base em ritmo. Master’s thesis, University of Coimbra.Google Scholar

  • Gonçalo Oliveira, H. 2012. PoeTryMe: a versatile platform for poetry generation. In Proceedings of ECAI 2012 Workshop on Computational Creativity, Concept Invention, and General Intelligence, Montpellier, France, C3GI 2012.Google Scholar

  • Gonçalo Oliveira, H., and Cardoso, A. 2015. Poetry generation with PoeTryMe. In Besold, T. R.; Schorlemmer, M.; and Smaill, A., eds., Computational Creativity Research: Towards Creative Machines, Atlantis Thinking Machines. Atlantis-Springer. chapter 12, 243–266.Google Scholar

  • Lerdahl, F., and Jackendoff, R. 1983. A generative theory of tonal music. Cambridge. MA: The MIT Press.Google Scholar

  • Manurung, H. 2003. An evolutionary algorithm approach to poetry generation. Ph.D. Dissertation, University of Edinburgh.Google Scholar

  • Misztal, J., and Indurkhya, B. 2014. Poetry Generation System With an Emotional Personality. In Proceedings of 5th International Conference on Computational Creativity, Ljubljana, Slovenia, ICCC 2014.Google Scholar

  • Nakamura, C., and Onisawa, T. 2009. Music/lyrics composition system considering user’s image and music genre. In Proceedings of 2009 IEEE international Conference on Systems, Man and Cybernetics, 1764–1769. San Antonio, TX, USA: IEEE Press.Google Scholar

  • Netzer, Y.; Gabay, D.; Goldberg, Y.; and Elhadad, M. 2009. Gaiku: generating Haiku with word associations norms. In Proceedings of the NAACL 2009 Workshop on Computational Approaches to Linguistic Creativity, CALC ’09, 32–39. Boulder, Colorado: ACL Press.Google Scholar

  • Newman, D.; Lau, J. H.; Grieser, K.; and Baldwin, T. 2010. Automatic Evaluation of Topic Coherence. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, HLT ’10, 100–108. Los Angeles, CA, USA: ACL Press.Google Scholar

  • Ramakrishnan A, A., and Devi, S. L. 2010. An alternate approach towards meaningful lyric generation in Tamil. In Proceedings of NAACL HLT 2010 2nd Workshop on Computational Approaches to Linguistic Creativity, CALC ’10, 31–39. Los Angeles, CA, USA: ACL Press.Google Scholar

  • Shen, H.-C. 2013. Lyrical Generation for a MIDI-to-Singing System. Advanced Science Letters 19(7):1852–1856.Google Scholar

  • Smith, M. R.; Hintze, R. S.; and Ventura, D. 2014. Nehovah: A Neologism Creator Nomen Ipsum. In Proceedings of 5th International Conference on Computational Creativity, Ljubljana, Slovenia, ICCC 2014.Google Scholar

  • Toivanen, J. M.; Järvisalo, M.; and Toivonen, H. 2013. Harnessing Constraint Programming for Poetry Composition. In Proceedings of the 4th International Conference on Computational Creativity, ICCC 2013, 160–167. Sydney, Australia: The University of Sydney.Google Scholar

  • Toivanen, J. M.; Toivonen, H.; and Valitutti, A. 2013. Automatical Composition of Lyrical Songs. In Proceedings of 4th International Conference on Computational Creativity, ICCC 2013, 87–91. Sydney, Australia: The University of Sydney.Google Scholar

  • Tomašič, P.;Žnidaršič, M.; and Papa, G. 2014. Implementation of a slogan generator. In Proceedings of 5th International Conference on Computational Creativity, Ljubljana, Slovenia, ICCC 2014, 340 – 343.Google Scholar

  • Turney, P. D. 2001. Mining the Web for Synonyms: PMI–IR versus LSA on TOEFL. In Proceedings of 12th European Conference on Machine Learning, ECML 2001, volume 2167 of LNCS, 491–502. Freiburg, Germany: Springer.Google Scholar

  • Veale, T., and Hao, Y. 2008. A Fluid Knowledge Representation for Understanding and Generating Creative Metaphors. In Proceedings of 22nd International Conference on Computational Linguistics, volume 1 of COLING ’08, 945–952. Manchester, UK: ACL Press.Google Scholar

About the article

Received: 2015-05-17

Accepted: 2015-11-19

Published Online: 2015-12-30

Published in Print: 2015-12-01


Citation Information: Journal of Artificial General Intelligence, ISSN (Online) 1946-0163, DOI: https://doi.org/10.1515/jagi-2015-0005.

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© 2015 Hugo Gonçalo Oliveira, published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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