Extending Monolingual Semantic Textual Similarity Task to Multiple Cross-lingual Settings

被引:0
作者
Hayashi, Yoshihiko [1 ]
Luo, Wentao [2 ]
机构
[1] Waseda Univ, Fac Sci & Engn, Shinjuku Ku, 2-4-12 Ohukubo, Tokyo 1690072, Japan
[2] Osaka Univ, Grad Sch Language & Culture, 1-8 Machikaneyama, Toyonaka, Osaka 5600043, Japan
来源
LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | 2016年
关键词
semantic textual similarity; STS; cross-lingual semantic similarity; machine translation quality;
D O I
暂无
中图分类号
H [语言、文字];
学科分类号
05 ;
摘要
This paper describes our independent effort for extending the monolingual semantic textual similarity (STS) task setting to multiple cross-lingual settings involving English, Japanese, and Chinese. So far, we have adopted a "monolingual similarity after translation" strategy to predict the semantic similarity between a pair of sentences in different languages. With this strategy, a monolingual similarity method is applied after having (one of) the target sentences translated into a pivot language. Therefore, this paper specifically details the required and developed resources to implement this framework, while presenting our current results for English-Japanese-Chinese cross-lingual STS tasks that may exemplify the validity of the framework.
引用
收藏
页码:1233 / 1239
页数:7
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