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        <title>Statistical machine translation adding pattern-based machine translation in Chinese-English translation</title>
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    <name type="personal">
        <namePart type="given">Jin’ichi</namePart>
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        <namePart type="given">Masato</namePart>
        <namePart type="family">Tokuhisa</namePart>
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    <name type="personal">
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        <namePart type="family">Ikehara</namePart>
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            <title>Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign</title>
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    <abstract>We have developed a two-stage machine translation (MT) system. The first stage is a rule-based machine translation system. The second stage is a normal statistical machine translation system. For Chinese-English machine translation, first, we used a Chinese-English rule-based MT, and we obtained ”ENGLISH” sentences from Chinese sentences. Second, we used a standard statistical machine translation. This means that we translated ”ENGLISH” to English machine translation. We believe this method has two advantages. One is that there are fewer unknown words. The other is that it produces structured or grammatically correct sentences. From the results of experiments, we obtained a BLEU score of 0.3151 in the BTEC-CE task using our proposed method. In contrast, we obtained a BLEU score of 0.3311 in the BTEC-CE task using a standard method (moses). This means that our proposed method was not as effective for the BTEC-CE task. Therefore, we will try to improve the performance by optimizing parameters.</abstract>
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        <url>https://aclanthology.org/2009.iwslt-evaluation.16</url>
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            <start>107</start>
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%0 Conference Proceedings
%T Statistical machine translation adding pattern-based machine translation in Chinese-English translation
%A Murakami, Jin’ichi
%A Tokuhisa, Masato
%A Ikehara, Satoru
%S Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign
%D 2009
%8 dec 1 2
%C Tokyo, Japan
%F murakami-etal-2009-statistical
%X We have developed a two-stage machine translation (MT) system. The first stage is a rule-based machine translation system. The second stage is a normal statistical machine translation system. For Chinese-English machine translation, first, we used a Chinese-English rule-based MT, and we obtained ”ENGLISH” sentences from Chinese sentences. Second, we used a standard statistical machine translation. This means that we translated ”ENGLISH” to English machine translation. We believe this method has two advantages. One is that there are fewer unknown words. The other is that it produces structured or grammatically correct sentences. From the results of experiments, we obtained a BLEU score of 0.3151 in the BTEC-CE task using our proposed method. In contrast, we obtained a BLEU score of 0.3311 in the BTEC-CE task using a standard method (moses). This means that our proposed method was not as effective for the BTEC-CE task. Therefore, we will try to improve the performance by optimizing parameters.
%U https://aclanthology.org/2009.iwslt-evaluation.16
%P 107-112

Markdown (Informal)

[Statistical machine translation adding pattern-based machine translation in Chinese-English translation](https://aclanthology.org/2009.iwslt-evaluation.16) (Murakami et al., IWSLT 2009)

• Statistical machine translation adding pattern-based machine translation in Chinese-English translation (Murakami et al., IWSLT 2009)

ACL

• Jin’ichi Murakami, Masato Tokuhisa, and Satoru Ikehara. 2009. Statistical machine translation adding pattern-based machine translation in Chinese-English translation. In Proceedings of the 6th International Workshop on Spoken Language Translation: Evaluation Campaign, pages 107–112, Tokyo, Japan.