Multi-Tiered Cantonese Word Segmentation

Charles Lam, Chaak Ming Lau, Jackson L. Lee

Abstract: Word segmentation for Chinese text data is essential for compiling corpora and any other tasks where the notion of “word” is assumed, since Chinese orthography does not have conventional word boundaries as languages such as English do. A perennial issue, however, is that there is no consensus about the definition of “word” in Chinese, which makes word segmentation challenging. Recent work in Chinese word segmentation has begun to embrace the idea of multiple word segmentation possibilities. In a similar spirit, this paper focuses on Cantonese, another major Chinese variety. We propose a linguistically motivated, multi-tiered word segmentation system for Cantonese, and release a Cantonese corpus of 150,000 characters word-segmented by this proposal. Our work will be of interest to researchers whose work involves Cantonese corpus data.