Improved approaches of modeling and detecting Error Patterns with empirical analysis for Computer-Aided Pronunciation Training

摘要

Error pattern detection is very helpful in Computer-Aided Pronunciation Training (CAPT). This paper reports the work of modeling and detecting Error Patterns defined by language teachers based on their linguist knowledge and pedagogical experiences. We develop a model generation framework to create the Error Pattern models from existing phoneme models. We also propose a serial structure for integrating Goodness-of-Pronunciation with the Error Pattern detectors. Experimental results and analysis over different approaches for modeling and detecting Error Patterns are presented, and it is found that both the binary classification error rates and the capability of Error Pattern diagnosis can be improved effectively with the proposed approaches.