15th Annual Conference of the International Speech Communication Association

September 14-18, 2014

A Comparison of GMM-HMM and DNN-HMM Based Pronunciation Verification Techniques for Use in the Assessment of Childhood Apraxia of Speech

Mostafa Shahin (1), Beena Ahmed (1), Jacqueline McKechnie (2), Kirrie Ballard (2), Ricardo Gutierrez-Osuna (3)

(1) Texas A&M University, Qatar
(2) University of Sydney, Australia
(3) Texas A&M University, USA

This paper introduces a pronunciation verification method to be used in an automatic assessment therapy tool of child disordered speech. The proposed method creates a phone-based search lattice that is flexible enough to cover all probable mispronunciations. This allows us to verify the correctness of the pronunciation and detect the incorrect phonemes produced by the child. We compare between two different acoustic models, the conventional GMM-HMM and the hybrid DNN-HMM. Results show that the hybrid DNN-HMM outperforms the conventional GMM-HMM for all experiments on both normal and disordered speech. The total correctness accuracy of the system at the phoneme level is above 85% when used with disordered speech.

Full Paper

Bibliographic reference.  Shahin, Mostafa / Ahmed, Beena / McKechnie, Jacqueline / Ballard, Kirrie / Gutierrez-Osuna, Ricardo (2014): "A comparison of GMM-HMM and DNN-HMM based pronunciation verification techniques for use in the assessment of childhood apraxia of speech", In INTERSPEECH-2014, 1583-1587.