Development of a Computer-Aided Pronunciation Training System for Teaching Mandarin for German Learners - Pronunciation Errors

This paper reports on the continued activities towards the development of a computer-aided language learning (CALL) system for German learners of Mandarin. In this experiment the method for detecting the pronunciation errors which was presented in a previous experiment was tested on two different databases in order to study the effect of complexity of corpus on the results of pronunciation error detection. The first corpus is simple and consists of monosyllabic and disyllabic words and read from German students of Mandarin in the first year of language education. The second corpus is more complex and consists of whole sentences and read from German students from three different years of language education. The data are perceptually evaluated by human judges as well as processed by two Automatic Speech Recognition (ASR) systems. Acoustic model of the first ASR system trained on data of native speakers of Mandarin. The second ASR system used an adapted acoustic model that considers the errors expected from the German learners of Mandarin. The experimental results show that the performance of the modified ASR system is better. The ratings of strength of foreign accent and intelligibility are strongly correlated with the correctness of tones than with the correctness of initials and finals. The ratio of correct initials and finals in the complex corpus is greater than in the simple corpus, but the number of correct tones is lower in the complex corpus.