THUTR: A Translation Retrieval System
نویسندگان
چکیده
We introduce a translation retrieval system THUTR, which casts translation as a retrieval problem. Translation retrieval aims at retrieving a list of target-language translation candidates that may be helpful to human translators in translating a given source-language input. While conventional translation retrieval methods mainly rely on parallel corpus that is difficult and expensive to collect, we propose to retrieve translation candidates directly from target-language documents. Given a source-language query, we first translate it into target-language queries and then retrieve translation candidates from target language documents. Experiments on Chinese-English data show that the proposed translation retrieval system achieves 95.32% and 92.00% in terms of P@10 at sentence level and phrase level tasks, respectively. Our system also outperforms a retrieval system that uses parallel corpus significantly. TITLE AND ABSTRACT IN CHINESE THUTRμÈ©u¢XÚ ·0 È©u¢XÚTHUTR"TXÚòÈÀu¢ ̄K"È©u¢ 3Ñ\ ó© |¢|ÿÀȧÈ< JøÏ"DÚ È©u¢{ ÌÄuV ¥§Ù¡ Ì ̄K ́ ïV ¥dp["d§·JѦ ^ü ¥¢yÈ©u¢"1⁄2 ó Χ·ÄkòÙȤ8Ió Χ, 2lü ¥¥u¢ÿÀÈ©"3Ç=êâþ ¢ L2§·JÑ È©u¢XÚ© O3éf?Úá? 95.32%Ú92.00% P@10"· XÚwÍL ¦^21 ¥ È©u¢XÚ"
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