Corpus-based learning of Cantonese for Mandarin speakers

This article presents the first study on using a parallel corpus to teach Cantonese, the variety of Chinese spoken in Hong Kong. We evaluated this approach with Mandarin-speaking undergraduate students at the beginner level. Exploiting their knowledge of Mandarin, a closely related language, the students studied Cantonese with authentic material in a Cantonese-Mandarin parallel corpus, transcribed from television programs. They were given a list of Mandarin words that yield a range of possible Cantonese translations, depending on the linguistic context. Leveraging sentence and word alignments in the parallel corpus, the students independently searched for example sentences to discover these translation equivalents. Experimental results showed that, in both the short- and long-term, this data-driven learning approach helped students improve their knowledge of Cantonese vocabulary. These results suggest the potential of applying parallel corpora at even the beginners' level for other L1-L2 pairs of closely related languages.