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Automatic Tamil lyric generation based on ontological interpretation for semantics

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Abstract

This system proposes an N-gram based approach to automatic Tamil lyric generation, by the ontological semantic interpretation of the input scene. The approach is based on identifying the semantics conveyed in the scenario, thereby making the system understand the situation and generate lyrics accordingly. The heart of the system includes the ontological interpretation of the scenario, and the selection of the appropriate tri-grams for generating the lyrics. To fulfill this, we have designed a new ontology with weighted edges, where the edges correspond to a set of sentences, which indicate a relationship, and are represented as a tri-gram. Once the appropriate tri-grams are selected, the root words from these tri-grams are sent to the morphological generator, to form words in their packed form. These words are then assembled to form the final lyrics. Parameters of poetry like rhyme, alliteration, simile, vocative words, etc., are also taken care of by the system. Using this approach, we achieved an average accuracy of 77.3% with respect to the exact semantic details being conveyed in the generated lyrics.

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References

  • Ananth Ramakrishnan A, Kuppan S and Sobha L D 2009 Automatic generation of Tamil lyrics for melodies. In: Proc. NAACL HLT Workshop on Computational Approaches to Linguistic Creativity (CALC), pp. 40–46

  • Apte C and Weiss S 1997 Data Mining with Decision Trees and Decision Rules. In: Future generation computer systems, vol. 13, No. 2–3, pp. 197–210

  • Bowra C M 1961 Greek Lyric Poetry - From Alcman to Simonides, Oxford University Press

  • Hirschman L and Gaizauskas R 2002 Natural language question answering: the view from here. J. Natural Language Eng. 7(4): 275–300

    Google Scholar 

  • Karthika R, Geetha T V, Ranjani P and Karky M 2011 Lyric Mining: Word, Rhyme & Concept Co-occurrence Analysis. In: Proc. Internat. Tamil Internet Conf., 2011, pp. 276–281

  • Mahalingam K and Huhns M N 1998 Representing and Using Ontologies, Center for Information Technology, Thesis, University of South Carolina

  • Mann C W and Moore A J 1981 Computer Generation of Multiparagraph English text. American J. Comput. Linguist. 7(1): 17–29

    Google Scholar 

  • Oliveira H G 2009 Portugal PoeTryMe: Towards Meaningful Poetry Generation, Dissertation, Universidade de Coimbra Portugal

  • Pandian L S and Geetha T V 2009 Semantic Role based Tamil Sentence Generator. In: Internat. Conf. on Asian Languages Processing, pp. 80–85

  • Sobha L D and Ananth Ramakrishnan A 2010 An alternate approach to meaningful lyric generation in Tamil. In: Proc. NAACL HLT 2010 Second Workshop on computational Approaches to Linguistic Creativity, pp. 31–39

  • Spyns P, Meersman R and Jarrar M 2002 Data modelling versus ontological engineering. Special Issue of SIGMOD Record on Semantic Web, Database Management and Information Systems 31(4): 12–17

    Google Scholar 

  • Sridhar R et al 2012a Lyric Generation, http://www.facebook.com/LyricGeneration

  • Sridhar R, Jalin Gladis D, Ganga K and Dhivya Prabha G 2012b N-gram based approach to automatic Tamil lyric generation by identifying emotion. In: Proceedings of International Conference on Advances in Computing, 2012, pp. 919–926

  • Suriyah M, Karky M, Geetha T V and Parthasarathi R 2011 Special Indices for LaaLaLaa Lyric Analysis & Generation Framework. In: Proc. Internat. Tamil Internet Conf., pp. 287–292

  • Thomas C H, Leiserson C E, Rivest R L and Stein C 2008 Introduction to algorithms, Prentice Hall of India

  • Weiss M A 2006 Data Structures and algorithms analysis in C, Pearson Education, India

  • Wong T M 2008 Automatic Generation of Modern Haiku Poetry, Dissertation, City University of Hong Kong

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Acknowledgements

We thank the Coordinator, Tamil Computing Lab, Department of Computer Science and Engineering (DCSE), Anna University, Chennai for providing the morphological analyzer module.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Anna University, Chennai, 600 025, India

    RAJESWARI SRIDHAR, D JALIN GLADIS, KAMESWARAN GANGA & G DHIVYA PRABHA

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  1. RAJESWARI SRIDHAR
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  2. D JALIN GLADIS
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  3. KAMESWARAN GANGA
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  4. G DHIVYA PRABHA
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Correspondence to RAJESWARI SRIDHAR.

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SRIDHAR, R., GLADIS, D.J., GANGA, K. et al. Automatic Tamil lyric generation based on ontological interpretation for semantics. Sadhana 39, 97–121 (2014). https://doi.org/10.1007/s12046-013-0209-2

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  • DOI: https://doi.org/10.1007/s12046-013-0209-2

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