Automatic Segmentation of Words using Syllable Bigram Statistics

We present a syllable bigram model for segmenting a Korean sentence into words and correcting word-spacing errors in the spelling checker. We evaluated the system’s performance for automatic word segmentation, word-spacing error detection, and the word-splitting problem of the character recognition system at the end of a line.

• Type: Conference
• Year: 2001
• Where: NLPRS
• Authors: Seung-Shik Kang, Chong-Woo Woo
• Keywords: Automatic Word Segmentation, Natural Language Processing, NLPRS 2001, Syllable Bigram Model, Word-spacing Error