• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Maximum Likelihood-based Automatic Lexicon Generation for AI Assistant-based Interaction with Mobile Devices


Abstract

In this paper, maximum likelihood-based automatic lexicon generation using mixed-syllables is proposed for unlimited vocabulary voice interface for East Asian languages (e.g. Korean, Chinese and Japanese) in AI-assistant based interaction with mobile devices. The conventional lexicon has two inevitable problems: 1) a tedious repetition of out-of-lexicon unit additions to the lexicon, and 2) the propagation of errors during a morpheme analysis and space segmentation. The proposed method provides an automatic framework to solve the above problems. The proposed method produces a level of overall accuracy similar to one of previous methods in the presence of one out-of-lexicon word in a sentence, but the proposed method provides superior results with the absolute improvements of 1.62%, 5.58%, and 10.09% in terms of word accuracy when the number of out-of-lexicon words in a sentence was two, three and four, respectively.


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Cite this article

[IEEE Style]
Donghyun Lee, Jae-Hyun Park, Kwang-Ho Kim, Jeong-Sik Park, Ji-Hwan Kim, Gil-Jin Jang and Unsang Park, "Maximum Likelihood-based Automatic Lexicon Generation for AI Assistant-based Interaction with Mobile Devices," KSII Transactions on Internet and Information Systems, vol. 11, no. 9, pp. 4264-4279, 2017. DOI: 10.3837/tiis.2017.09.005

[ACM Style]
Lee, D., Park, J., Kim, K., Park, J., Kim, J., Jang, G., and Park, U. 2017. Maximum Likelihood-based Automatic Lexicon Generation for AI Assistant-based Interaction with Mobile Devices. KSII Transactions on Internet and Information Systems, 11, 9, (2017), 4264-4279. DOI: 10.3837/tiis.2017.09.005