Automatic Mandarin pronunciation scoring for native learners with dialect accent

This paper studies pronunciation scoring algorithm in CALL system aiming at teaching native Chinese learn standard Mandarin. Most of the pronunciation scoring algorithms focus on non-native environment, which may not be suitable for native speakers. We bring up a new algorithm based on traditional posterior log-likelihood algorithm by weighting the initial part of Mandarin syllables, where final-initial’s duration ratio is introduced to control the weight. Experiments show that the proposed algorithm is much more effective than traditional posterior log-likelihood algorithm in the Mandarin learning system. The correlation with human score achieves an increase of 11%.