Application of LVCSR to the Detection of Chinese Mandarin Reading Miscues

For a reading tutor, the most important task is to detect the reading miscues such as insertions, omissions, etc. This paper constructed a Chinese reading miscues detection system based on technologies of general large vocabulary continuous speech recognition and proposed two methods to improve the performance of the detection. The first is to align the reference to the confusion network resulted from the recognition instead of the 1-best result to find out the reading miscues. And the second is using the knowledge of reference to regulate the decoding by weighting the n-gram language model probability, if it exists in the reference. The experiments on a Chinese Mandarin reading corpus proved the effectiveness of these two modifications. The detection MDerr and FArate are depressed 50.1% and 70.8% totally by these two methods.