WEKO3
アイテム
A Simple and Effective Method for Injecting Word-level Information into Character-aware Neural Language Models
http://hdl.handle.net/10061/0002000643
http://hdl.handle.net/10061/0002000643e920854b-d425-4275-8d0f-661916dbadff
| アイテムタイプ | 学術雑誌論文 / Journal Article(1) | |||||||||||
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| 公開日 | 2024-10-25 | |||||||||||
| タイトル | ||||||||||||
| タイトル | A Simple and Effective Method for Injecting Word-level Information into Character-aware Neural Language Models | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ | journal article | |||||||||||
| アクセス権 | ||||||||||||
| アクセス権 | open access | |||||||||||
| 著者 |
Feng, Yukun
× Feng, Yukun
× 上垣外, 英剛× Takamura, Hiroya
× Okumura, Manabu
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| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | In this study, we propose a simple and effective method to inject word-level information into character-aware neural language models. Unlike previous approaches, which typically inject word-level information as input to a long short-term memory (LSTM) network, we inject such information into the softmax function. The resultant model can be considered a combination of a character-aware language model and a simple word-level language model. Our injection method can be used in conjunction with previous methods. The results of experiments on 14 typologically diverse languages are provided to empirically show that our injection method performed better than previous methods that inject word-level information at the input, including a gating mechanism, averaging, and concatenation of word vectors. Our method can also be used together with previous injection methods. Finally, we provide a comprehensive comparison with previous injection methods and analyze the effectiveness of word-level information in character-aware language models and the properties of our injection method in detail. | |||||||||||
| 書誌情報 |
ja : 自然言語処理 巻 30, 号 1, p. 156-183, 発行日 2023-03-15 |
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| 出版者 | ||||||||||||
| 出版者 | 言語処理学会 | |||||||||||
| ISSN | ||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||
| 収録物識別子 | 2185-8314 | |||||||||||
| 出版者版DOI | ||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.5715/jnlp.30.156 | |||||||||||
| 出版者版URI | ||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||
| 識別子タイプ | URI | |||||||||||
| 関連識別子 | https://www.jstage.jst.go.jp/article/jnlp/30/1/30_156/_article/-char/ja/ | |||||||||||
| 権利 | ||||||||||||
| 権利情報Resource | https://creativecommons.org/licenses/by/4.0/ | |||||||||||
| 権利情報 | $00A9 2023 The Association for Natural Language Processing. Licensed under CC BY 4.0(https://creativecommons.org/licenses/by/4.0/). | |||||||||||
| 著者版フラグ | ||||||||||||
| 出版タイプ | NA | |||||||||||
