Linear-Time Korean Morphological Analysis Using an Action-based Local Monotonic Attention Mechanism

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3
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3

초록

For Korean language processing, morphological analysis is a critical component that requires extensive work. This morphological analysis can be conducted in an end-to-end manner without requiring a complicated feature design using a sequence-to-sequence model. However, the sequence-to-sequence model has a time complexity of O(n(2)) for an input length n when using the attention mechanism technique for high performance. In this study, we propose a linear-time Korean morphological analysis model using a local monotonic attention mechanism relying on monotonic alignment, which is a characteristic of Korean morphological analysis. The proposed model indicates an extreme improvement in a single threaded environment and a high morphometric F1-measure even for a hard attention model with the elimination of the attention mechanism formula.

키워드

deep learningkorean morphological analysislocal attention mechanismnatural language processingsequence-to-sequence learning
제목
Linear-Time Korean Morphological Analysis Using an Action-based Local Monotonic Attention Mechanism
저자
Hwang, HyunsunLee, Changki
DOI
10.4218/etrij.2018-0456
발행일
2020-02
유형
Article
저널명
ETRI Journal
42
1
페이지
101 ~ 107