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Indexed by:会议论文

Date of Publication:2019-01-01

Included Journals:CPCI-S、EI

Page Number:363-371

Key Words:Heterographic Pun Recognition; Pronunciation; Spelling; Gated Attention

Abstract:Heterographic pun plays a critical role in human writing and literature, which usually has a similar sounding or spelling structure. It is important and difficult research to recognize the heterographic pun because of the ambiguity. However, most existing methods for this task only focus on designing features with rule-based or machine learning methods. In this paper, we propose an end-to-end computational approach Pronunciation Spelling Understanding Gated Attention (PSUGA) network. For pronunciation, we exploit the hierarchical attention model with phoneme embedding. While for spelling, we consider the character-level, word-level, tag-level, position-level and contextual-level embedding with attention model. To deal with the two parts, we present a gated attention mechanism to control the information integration. We have conducted extensive experiments on SemEva12017 task7 and Pun of the Day datasets. Experimental results show that our approach significantly outperforms state-of-the-art methods.