This paper describes our recent work on the development of a large-vocabulary, speaker-independent continuous speech recognition system for Cantonese (a major Chinese dialect). Both acoustic modeling and language modeling are being addressed. For acoustic modeling, we focus on right-context-dependent sub-syllable units. Tying of HMM at model as well as state level is applied based on phonetic knowledge and the decision-tree approach. Statistical language model is built from large amount of newspaper text. The overall recognition accuracy for syllable and Chinese character are 81.83% and 68.94% respectively.