Forward optimal measures for automatic mispronunciation detection

Pronunciation measure computation is a vital part of Computer Assisted Pronunciation Training (CAPT) system. This paper conducts some research on pronunciation measures based on the two popular measures - Log posterior probability (LPP) and Goodness of Pronunciation (GOP). A modified GOP - AGOP is proposed which directly uses the segmentation information of forced alignment instead of free phone recognizer (FPR) when computing the denominator of GOP to avoid the effect of inaccuracy of FPR. The context dependent acoustic models is investigated in mispronunciation detection. It is found that Tri-phone AM has better performance in mispronunciation detection of continuous speech. This paper also proposes a fast algorithm of pronunciation measure - FAGOP which uses the maximization instead of summation to calculate the denominator of AGOP approximately and applies Viterbi algorithm with some effective pruning strategy to reduce the computation perplexity. It achieves much better efficiency while barely impairing the detection presicion.