Dealing with Multilinguality in a Spoken Language Query Translator

In this paper, we examine three issues concerning the robustness of multilingual speech interfaces for spoken language translation systems: accent differences, mixed language input, and the use of common feature sets for HMM-based speech recognizers for English and Cantonese. From the results of our preliminary experiments, we find that accent difference causes recognizers performance to degrade. For mixed language input, we found out that a straight forward implementation of a mixed language model-based speech recognizer performs less well than the concatenation of pure language recognizers due to the increase in recognition candidate numbers. Finally, our experimental results show that the Cantonese recognizer has a lower recognition rate on the average than the English recognizer despite a common feature set, parameter set, and common algorithm.