An LSTM Method for Natural Pronunciation Expression of Foreign Words in Sentences


KIPS Transactions on Software and Data Engineering, Vol. 8, No. 4, pp. 163-170, Apr. 2019
https://doi.org/10.3745/KTSDE.2019.8.4.163,   PDF Download:
Keywords: Postposition, LSTM, Dropout, Overfitting, Final Consonant Pronunciation of Nouns
Abstract

Korea language has postpositions such as eul, reul, yi, ga, wa, and gwa, which are attached to nouns and add meaning to the sentence. When foreign notations or abbreviations are included in sentences, the appropriate postposition for the pronunciation of the foreign words may not be used. Sometimes, for natural expression of the sentence, two postpositions are used with one in parentheses as in “eul(reul)” so that both postpositions can be acceptable. This study finds examples of using unnatural postpositions when foreign words are included in Korean sentences and proposes a method for using natural postpositions by learning the final consonant pronunciation of nouns. The proposed method uses a recurrent neural network model to naturally express postpositions connected to foreign words. Furthermore, the proposed method is proven by learning and testing with the proposed method. It will be useful for composing perfect sentences for machine translation by using natural postpositions for English abbreviations or new foreign words included in Korean sentences in the future.


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Cite this article
[IEEE Style]
S. Kim and J. Jung, "An LSTM Method for Natural Pronunciation Expression of Foreign Words in Sentences," KIPS Transactions on Software and Data Engineering, vol. 8, no. 4, pp. 163-170, 2019. DOI: https://doi.org/10.3745/KTSDE.2019.8.4.163.

[ACM Style]
Sungdon Kim and Jaehee Jung. 2019. An LSTM Method for Natural Pronunciation Expression of Foreign Words in Sentences. KIPS Transactions on Software and Data Engineering, 8, 4, (2019), 163-170. DOI: https://doi.org/10.3745/KTSDE.2019.8.4.163.