Construction of intelligent evaluation model for Topic Talk in the Mandarin proficiency test

In order to solve the problem that the Topic Talk in the Mandarin proficiency test is still unable to achieve machine evaluation, an intelligent evaluation model for Topic Talk is constructed in this paper. First, according to the requirements of the intelligent evaluation model, a large vocabulary continuous speech recognition module is designed in the front of the model. Then the recognition module is optimized from the two aspects of the acoustic model and the language model. Finally, the experiment is performed on the dataset which is collected from the Mandarin Proficiency Test Center. The experimental results show that the speech recognition module constructed with the improved DBLSTM-HMM acoustic model and n-gram+RNN interpolation language model can better complete the recognition task of front part in the intelligent evaluation model. The improved acoustic model can reduce the word error rate and sentence error rate to 14.08% and 18.22%. The improved language model can increase the word recognition rate by 5.87%, and the correlation between the posterior probability and the manual score by 3.82%.