Abstract
Machine translation for social communication is necessary in daily life. However, spoken language translation faces many challenges especially in the translation of zero pronouns which is absent in the source language but appear in the target language. Dropping of pronouns severely affects the machine translation from pronoun dropped language such as Chinese to other languages. This phenomenon occurs more frequently in the conversational spoken language. In order to solve this problem, we insert the position of missing pronouns into the source side, then we use the word alignment method to filter the pronouns in order to pick up the pronouns which are really helpful for the machine translation. We achieve improvement on the translation of chat, message and telephone conversational corpus.
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Notes
- 1.
This corpus comes from the DARPA Broad Operational Language Translation (BOLT) Program which includes message, chat,and telephone conversation parallel data sets The website is https://www.ldc.upenn.edu/sites/www.ldc.upenn.edu/files/bolt_1.pdf.
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Acknowledgments
This work is supported by the National Basic Research Program of China (973 Program, Grant No. 2013CB329303), the National Natural Science Foundation of China (Grant No. 61132009, 61202244) and Beijing Institute of Technology Research Fund Program for Young Scholars.
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Hu, Y., Huang, H., Jian, P., Guo, Y. (2015). Improving Conversational Spoken Language Machine Translation via Pronoun Recovery. In: Zhang, X., Sun, M., Wang, Z., Huang, X. (eds) Social Media Processing. SMP 2015. Communications in Computer and Information Science, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-0080-5_20
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DOI: https://doi.org/10.1007/978-981-10-0080-5_20
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