Second language speech recognition using multiple-pass decoding with lexicon represented by multiple reduced phoneme sets

Considering that the pronunciation of second language speech is usually influenced by the mother tongue, we previously proposed using a reduced phoneme set for second language when the mother tongue of speakers is known. However, the proficiency of second language speakers varies widely, as does the influence of mother tongue on their pronunciation. Consequently, the optimal phoneme set is dependent on the proficiency of the second language speaker. In this work, we examine the relation between the proficiency of speakers and a reduced phoneme set customized for them. We propose a novel speech recognition method which is multiple-pass decoding using a lexicon represented by multiple reduced phoneme sets based on experimental results for speech recognition of second language speakers with various proficiencies. The relative error reduction obtained with the multiple reduced phoneme sets is 26.8% compared with the canonical one.