Multiple Reduced Phoneme Sets for Second Language Speech Recognition

This paper describes a novel method to improve the performance of second language speech recognition when the mother tongue of users is known. Considering that second language speech usually includes less fluent pronunciation and more frequent pronunciation mistakes, I propose using a reduced phoneme set generated by a phonetic decision tree (PDT)-based top-down sequential splitting method instead of the canonical one of the second language. However, the proficiency of second language speakers varies widely, the optimal phoneme set is dependent on the proficiency of the second language speaker. In this work, I verify the efficacy of reduced phoneme set in the first step, and examine the relation between the proficiency of speakers and a reduced phoneme set customized for them in the second step. On the basis of the results of the investigation, I propose a novel speech recognition method using multiple reduced phoneme sets to further improve the recognition performance considering the various proficiency levels of second language speakers. Experimental results demonstrate the high validity of the proposed method.