Automatic scoring of pronunciation quality
Speech Communication
Phone-level pronunciation scoring and assessment for interactive language learning
Speech Communication
Combination of machine scores for automatic grading of pronunciation quality
Speech Communication
Analysis of Hypernasal Speech in Children with Cleft Lip and Palate
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Utilizing cumulative logit models and human computation on automated speech assessment
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
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Automatic pronunciation scoring makes novel applications for computer assisted language learning possible. In this paper we concentrate on the feature extraction. A relatively large feature vector with 28 sentence- and 33 word-level features has been designed. On the word-level correctly and mispronounced words are classified, on the sentence-level utterances are rated with 5 discrete marks. The features are evaluated on two databases with non-native adults’ and children’s speech, respectively. Up to 72 % class-wise-averaged recognition rate is achieved for 2 classes; the result of the 5-class problem can be interpreted as 80 % recognition rate.