Detection of language boundary in code-switching utterances by bi-phone probabilities

In this paper, we present an effective method to detect the language boundary (LB) in code-switching utterances. The utterances are mainly produced in Cantonese, a commonly used Chinese dialect, whilst occasionally English words are inserted between Cantonese words. Bi-phone probabilities are calculated to measure the confidence that the recognized phones are in Cantonese. Two sets of context-independent mono-phone models are trained by monolingual Cantonese and monolingual English data separately. Both knowledge-based and data-driven model selection approaches are studied in order to retain the language-dependent characteristics and to merge duplicated phone sets between the two languages. The LB detection accuracy is 75.12% for utterances that contain one single code-switching word or phrase.