A realistic and robust model for Chinese word segmentation

Chu-ren Huang, Ting Shuo Yo, Simon Petr, Shu Kai Hsieh

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)


A realistic Chinese word segmentation tool must adapt to textual variations with minimal training input and yet robust enough to yield reliable segmentation result for all variants. Various lexicon-driven approaches to Chinese segmentation, e.g. [1,16], achieve high f-scores yet require massive training for any variation. Text-driven approach, e.g. [12], can be easily adapted for domain and genre changes yet has difficulty matching the high f-scores of the lexicon-driven approaches. In this paper, we refine and implement an innovative text-driven word boundary decision (WBD) segmentation model proposed in [15]. The WBD model treats word segmentation simply and efficiently as a binary decision on whether to realize the natural textual break between two adjacent characters as a word boundary. The WBD model allows simple and quick training data preparation converting characters as contextual vectors for learning the word boundary decision. Machine learning experiments with four different classifiers show that training with 1,000 vectors and 1 million vectors achieve comparable and reliable results. In addition, when applied to SigHAN Bakeoff 3 competition data, the WBD model produces OOV recall rates that are higher than all published results. Unlike all previous work, our OOV recall rate is comparable to our own F-score. Both experiments support the claim that the WBD model is a realistic model for Chinese word segmentation as it can be easily adapted for new variants with robust result. In conclusion, we will discuss linguistic ramifications as well as future implications for the WBD approach.
Original languageEnglish
Title of host publicationProceedings of the 20th Conference on Computational Linguistics and Speech Processing, ROCLING 2008
Number of pages14
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event20th Conference on Computational Linguistics and Speech Processing, ROCLING 2008 - Taipei, Taiwan
Duration: 4 Sep 20085 Sep 2008


Conference20th Conference on Computational Linguistics and Speech Processing, ROCLING 2008


  • Segmentation

ASJC Scopus subject areas

  • Language and Linguistics
  • Speech and Hearing

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