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This paper aims to find out an approach to autoscoring the Chinese-English interpretation testing speech, which is one of the important research areas, meets the demand of computer-assistant English testing and adds value to machine intelligence. We proposed a method to evaluate the semantic similarity based on Wordnet combining words and sentences, which was applied to recognizing the keywords and its synonym in testing speech via HMM model and calculating the score of semantic. In addition, speech fluency was also considered in our developed system and has a contribution to the final score. This paper collected 300 testing speech data from a course final examination in Guangdong University of Foreign Studies to examine the autoscoring system. Result has shown well performance of the average rate of speech recognition and agreement of system score and human score.

A Chinese-English Interpretation Testing Autoscoring System Based on Semantic Analysis