著者
Shohei Higashiyama Masao Utiyama Eiichiro Sumita Masao Ideuchi Yoshiaki Oida Yohei Sakamoto Isaac Okada Yuji Matsumoto
出版者
The Association for Natural Language Processing
雑誌
自然言語処理 (ISSN:13407619)
巻号頁・発行日
vol.27, no.3, pp.499-530, 2020-09-15 (Released:2020-12-15)
参考文献数
54

Although limited effort has been devoted to exploring neural models in Japanese word segmentation, much effort has been actively applied to Chinese word segmentation because of the ability to minimize effort in feature engineering. In this work, we propose a character-based neural model that makes joint use of word information useful for disambiguating word boundaries. For each character in a sentence, our model uses an attention mechanism to estimate the importance of multiple candidate words that contain the character. Experimental results show that learning attention to proper words leads to accurate segmentations and that our model achieves better performance than existing statistical and neural models on both in-domain and cross-domain Japanese word segmentation datasets.

言及状況

外部データベース (DOI)

Twitter (3 users, 3 posts, 11 favorites)

論文 "Character-to-Word Attention for Word Segmentation"(https://t.co/1i2FXgvvgv)に関して言語処理学会論文賞を頂きました。3/18(木) 16:10頃から招待論文にて、注意機構を用いたニューラル単語分割について、日本語データでの多ドメインの分析結果を紹介します。(発表は日本語です) #NLP2021

収集済み URL リスト