Automatic Phonetic Segmentation and Pronunciation Detection with Various Approaches of Acoustic Modeling

Abstract

The paper describes HMM-based phonetic segmentation realized by KALDI toolkit with the focus on study of accuracy of various acoustic modeling such as GMM-HMM vs. DNN-HMM, monophone vs. triphone, speaker independent vs. speaker dependent. The analysis was performed using TIMIT database and it proved the contribution of advanced acoustic modeling for the choice of a proper pronunciation variant. For this purpose, the lexicon covering the pronunciation variability among TIMIT speakers was created on the basis of phonetic transcriptions available in TIMIT corpus. When the proper sequence of phones is recognized by DNN-HMM system, more precise boundary placement can be then obtained using basic monophone acoustic models.