Syntactically annotated corpora have become important resources for natural language processing due in part to the success of corpus-based methods. Since words are often considered as primitive units of language structures, the annotation of word segmentation forms the basis of these corpora. This is also an issue for the Vietnamese Treebank (VTB), which is the first and only publicly available syntactically annotated corpus for the Vietnamese language. Although word segmentation is straight-forward for space-delimited languages like English, this is not the case for languages like Vietnamese for which a standard criterion for word segmentation does not exist. This work explores the challenges of Vietnamese word segmentation through the detection and correction of inconsistency for VTB. Then, by combining and splitting the inconsistent annotations that were detected, we are able to observe the influence of different word segmentation criteria on automatic word segmentation, and the applications of word segmentation, including text classification and English-Vietnamese statistical machine translation. The analysis and experimental results showed that our methods improved the quality of VTB, which positively affected the performance of its applications. Title and Abstract in another language, L2 (optional, and on same page) So sánh các tiêu chí tách từ khác nhau thông qua ứng dụng