The extraction of beautiful sound patterns from Sunthorn Phu’s poem using machine learning technique and internal rhyme rule

(1) * Pattarakorn Suksanguan Mail (Silpakorn University, Thailand)
(2) Sajjaporn Waijanya Mail (Silpakorn University, Thailand)
(3) Nuttachot Promrit Mail (Silpakorn University, Thailand)
*corresponding author

Abstract


The melodious poems have been written from the distinctive features of poetry or based on each country's typical style. Especially, Thai poems which composed by the use of specific forming, such as Internal Rhyme to develop melodiousness. The most attractive and well-known poems were composed by a genius Thai poet named Sunthorn Phu. He is a role model for Thai poets. UNESCO honored him as the world’s great poet and the best role model in poetry works. In this article, we proposed extracting 15,796 sentences (Waks) of the beautiful sound patterns of Phra Aphai Mani’s tales by machine learning technology in conjunction with the rules of internal Rhyme Klon-Suphap by using the Apriori Algorithm. The extraction of vowel rhymes separated by a group of Waks including 1) Poem Wak No. 1; 2) Poem Wak No. 2; 3) Poem Wak No. 3; and 4) Poem Wak No. 4. In this article, “Wak” means sentence. The created tool can extract the internal rhyme patterns and the 25 popular pattern vowels. The popular pattern illustrates the melodiousness of the Poem and sets up a standard of how to melodiously compose a poem. Then, the evaluation of the experiments was done by using 144 Waks selected from the extraction of the beautiful patterns and evaluated by the consistency score from 3 experts. The average accuracy score resulted in 95.30%.

Keywords


Machine Learning; Apriori Algorithm; Rule Base; Sunthorn Phu; Sound Pattern

   

DOI

https://doi.org/10.26555/ijain.v7i2.613
      

Article metrics

Abstract views : 299 | PDF views : 49

   

Cite

   

Full Text

Download

References


[1] S. Waijanya and N. Promrit, “The Poet Identification Using Convolutional Neural Networks,” 2018, pp. 179–187. doi: 10.1007/978-3-319-60663-7_17

[2] A. Meesing, “Book Review-The Journey to Petchburi: A Poem by Sunthorn Phu,” ABAC J., vol. 36, no. 2, pp. 135–139, 2016. Available at: Google Scholar.

[3] G. Li and J. Li, “Research on Sentiment Classification for Tang Poetry based on TF-IDF and FP-Growth,” in 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2018, pp. 630–634, doi: 10.1109/IAEAC.2018.8577715.

[4] R. Rajan and A. A. Raju, “Deep Neural Network Based Poetic Meter Classification Using Musical Texture Feature Fusion,” in 2019 27th European Signal Processing Conference (EUSIPCO), 2019, pp. 1–5, doi: 10.23919/EUSIPCO.2019.8902998.

[5] N. Promrit and S. Waijanya, “Convolutional Neural Networks for Thai Poem Classification,” 2017, pp. 449–456. doi: 10.1007/978-3-319-59072-1_53

[6] J. Kaur and J. R. Saini, “Punjabi poetry classification: the test of 10 machine learning algorithms,” in Proceedings of the 9th International Conference on Machine Learning and Computing, 2017, pp. 1–5. doi: 10.1145/3055635.3056589

[7] A. M. S. Rahma, M. A. H. Alrawi, and N. A. G., “A Novel Coding and Discremenation (CODIS) Algorithm to Extract Features from Arabic Texts to Discriminate Arabic Poems,” in 2018 1st Annual International Conference on Information and Sciences (AiCIS), 2018, pp. 117–128, doi: 10.1109/AiCIS.2018.00033.

[8] W.-C. Yeh, Y.-C. Chang, Y.-H. Li, and W.-C. Chang, “Rhyming Knowledge-Aware Deep Neural Network for Chinese Poetry Generation,” in 2019 International Conference on Machine Learning and Cybernetics (ICMLC), 2019, pp. 1–6, doi: 10.1109/ICMLC48188.2019.8949208.

[9] D. Liu, J. Lv, and Y. Li, “Generating Style-Specific Chinese Tang Poetry With a Simple Actor-Critic Model,” IEEE Trans. Emerg. Top. Comput. Intell., vol. 3, no. 4, pp. 313–321, Aug. 2019, doi: 10.1109/TETCI.2018.2870125.

[10] Y. Zhang, Y. Li, X. Wei, and L. Jia, “Adaptive spatio-temporal graph convolutional neural network for remaining useful life estimation,” in 2020 International joint conference on neural networks (IJCNN), 2020, pp. 1–7, doi: 10.1109/IJCNN48605.2020.

[11] N. Promrit, S. Waijanya, and K. Thaweesith, “The Evaluation of Thai Poem’s Content Consistency using Siamese Network,” in Proceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval, 2019, pp. 115–120, doi: 10.1145/3342827.3342855.

[12] S. Waijanya and A. Mingkhwan, “Thai poetry translation to English with backward translation evaluation,” in Ninth International Conference on Digital Information Management (ICDIM 2014), 2014, pp. 248–253, doi: 10.1109/ICDIM.2014.6991425.

[13] S. Seljan, I. Dunder, and M. Pavlovski, “Human Quality Evaluation of Machine-Translated Poetry,” in 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 2020, pp. 1040–1045, doi: 10.23919/MIPRO48935.2020.9245436.

[14] I. Dunder, S. Seljan, and M. Pavlovski, “Automatic Machine Translation of Poetry and a Low-Resource Language Pair,” in 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 2020, pp. 1034–1039, doi: 10.23919/MIPRO48935.2020.9245342.

[15] O. Khongtum, N. Promrit, and S. Waijanya, “The Entity Recognition of Thai Poem Compose by Sunthorn Phu by Using the Bidirectional Long Short Term Memory Technique,” 2019, pp. 97–108. doi: 10.1007/978-3-030-33709-4_9

[16] A. Mittmann, A. von Wangenheim, and A. L. dos Santos, “A Multi-level Visualization Scheme for Poetry,” in 2016 20th International Conference Information Visualisation (IV), 2016, pp. 312–317, doi: 10.1109/IV.2016.64.

[17] M. A. Ahmed and S. Trausan-Matu, “Using natural language processing for analyzing Arabic poetry rhythm,” in 2017 16th RoEduNet Conference: Networking in Education and Research (RoEduNet), 2017, pp. 1–5, doi: 10.1109/ROEDUNET.2017.8123759.

[18] W. Menninghaus, V. Wagner, E. Wassiliwizky, T. Jacobsen, and C. A. Knoop, “The emotional and aesthetic powers of parallelistic diction,” Poetics, vol. 63, pp. 47–59, 2017. doi: 10.1016/j.poetic.2016.12.001

[19] S. Harikumar and D. U. Dilipkumar, “Apriori algorithm for association rule mining in high dimensional data,” in 2016 International Conference on Data Science and Engineering (ICDSE), 2016, pp. 1–6, doi: 10.1109/ICDSE.2016.7823952.

[20] B. Li, Q. Ji, Z. Mi, Y. Yang, and Y. Guo, “An Improved Apriori Algorithm Applied to Mining Ancient Chinese Poems,” in 2018 International Conference on Computer, Information and Telecommunication Systems (CITS), 2018, pp. 1–5, doi: 10.1109/CITS.2018.8440132.

[21] J. Liu, F. Wu, C. Wu, Y. Huang, and X. Xie, “Neural Chinese word segmentation with dictionary,” Neurocomputing, vol. 338, pp. 46–54, Apr. 2019, doi: 10.1016/j.neucom.2019.01.085.

[22] Y. Wei, H. Wang, J. Zhao, Y. Liu, Y. Zhang, and B. Wu, “GeLaiGeLai: A visual platform for analysis of Classical Chinese Poetry based on Knowledge Graph,” in 2020 IEEE International Conference on Knowledge Graph (ICKG), 2020, pp. 513–520, doi: 10.1109/ICBK50248.2020.00078.

[23] S. Waijanya and A. Mingkhwan, “The Evaluations of Thai Poetry Translator to English with Prosody Keeping.,” J. Digit. Inf. Manag., vol. 12, no. 6, pp. 357–368, 2014. Available at: Google Scholar.

[24] D. D. McCracken and E. D. Reilly, “Backus-naur form (bnf),” in Encyclopedia of Computer Science, 2003, pp. 129–131. Available at: Google Scholar.

[25] J. Yabing, “Research of an Improved Apriori Algorithm in Data Mining Association Rules,” Int. J. Comput. Commun. Eng., pp. 25–27, 2013, doi: 10.7763/IJCCE.2013.V2.128.

[26] H. Turner, G. Lovisotto, and I. Martinovic, “Attacking speaker recognition systems with phoneme morphing,” in European Symposium on Research in Computer Security, 2019, pp. 471–492. doi: 10.1007/978-3-030-29959-0_23

[27] Sunee Leelapornpinit, “A comparative study of thai and chinese phonology for the use of basic thai language teaching as a foreign language,” Suthiparithat J., vol. 30, no. 93, pp. 33–46, 2016. Available at: Suthiparithat Journal

[28] H. Winskel and T. Ratitamkul, “The Initial Functional Unit When Naming Words and Pseudowords in Thai: Evidence from Masked Priming,” J. Psycholinguist. Res., vol. 49, no. 2, pp. 275–290, 2020. doi: 10.1007/s10936-020-09687-7




Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

___________________________________________________________
International Journal of Advances in Intelligent Informatics
ISSN 2442-6571  (print) | 2548-3161 (online)
Organized by Informatics Department - Universitas Ahmad Dahlan, and ASCEE Computer Society
Published by Universitas Ahmad Dahlan
W: http://ijain.org
E: ijain@uad.ac.id (paper handling issues)
    info@ijain.org, andri.pranolo.id@ieee.org (publication issues)

View IJAIN Stats

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0