Summary of the paper

Title Adapting Chinese Word Segmentation for Machine Translation Based on Short Units
Authors Yiou Wang, Kiyotaka Uchimoto, Jun’ichi Kazama, Canasai Kruengkrai and Kentaro Torisawa
Abstract In Chinese texts, words composed of single or multiple characters are not separated by spaces, unlike most western languages. Therefore Chinese word segmentation is considered an important first step in machine translation (MT) and its performance impacts MT results. Many factors affect Chinese word segmentations, including the segmentation standards and segmentation strategies. The performance of a corpus-based word segmentation model depends heavily on the quality and the segmentation standard of the training corpora. However, we observed that existing manually annotated Chinese corpora tend to have low segmentation granularity and provide poor morphological information due to the present segmentation standards. In this paper, we introduce a short-unit standard of Chinese word segmentation, which is particularly suitable for machine translation, and propose a semi-automatic method of transforming the existing corpora into the ones that can satisfy our standards. We evaluate the usefulness of our approach on the basis of translation tasks from the technology newswire domain and the scientific paper domain, and demonstrate that it significantly improves the performance of Chinese-Japanese machine translation (over 1.0 BLEU increase).
Topics Machine Translation, SpeechToSpeech Translation, Parsing, Standards for LRs
Full paper Adapting Chinese Word Segmentation for Machine Translation Based on Short Units
Slides -
Bibtex @InProceedings{WANG10.83,
  author = {Yiou Wang and Kiyotaka Uchimoto and Jun’ichi Kazama and Canasai Kruengkrai and Kentaro Torisawa},
  title = {Adapting Chinese Word Segmentation for Machine Translation Based on Short Units},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
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