Corpus Support for Machine Translation at LDC

نویسندگان

  • Xiaoyi Ma
  • Christopher Cieri
چکیده

This paper describes LDC's efforts in collecting, creating and processing different types of linguistic data, including lexicons, parallel text, multiple translation corpora, and human assessment of translation quality, to support the research and development in Machine Translation. Through a combination of different procedures and core technologies, the LDC was able to create very large, high quality, and cost-efficient corpora, which have contributed significantly to recent advances in Machine Translation. Multiple translation corpora and human assessment together facilitate, validate and improve automatic evaluation metrics, which are vital to the development of MT systems. The Bilingual Internet Text Search (BITS) and Champollion sentence aligner enable the finding and processing of large quantities of parallel text. All specifications and tools used by LDC and described in the paper are or will be available to the general public.

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تاریخ انتشار 2006