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1. Zarringhalam, Rojin Majd. Consonant Classification Based on Tongue Tip Trajectories.

Degree: MSc -MS, Computer Science, 2018, York University

In this thesis, I investigate an issue that is foundational to the development of a new class of novel game-based speech therapies. Whereas several prior computer-based approaches have focused on the use of clinical objectives that concern spatialized aspects of the tongue-tip trajectory (e.g., the targeting of improved accuracy in lingual-palate contact for certain phonemic segments), this line of inquiry focuses on the potential use of attributes relating to the speed and velocity of the tongue-tip trajectory as an alternative clinical objective. I situate my work in the body of prior work on the velocity characteristics of different phonemic segments. For speed and velocity-based clinical targets to be viable, however, it is necessary to characterize and to analyze the relative amounts of variability among and within talkers and phonemic segments with respect to speed-related characteristics. I describe our approach and the results of an analysis which focuses on a large kinematic speech dataset that includes multiple repetitions of 8 different phonemic segments (/t/, /d/, /k/, /g/) as plosives, (/s/, /sh/, /z/) as fricatives and (/tch/) as affricate by 17 talkers. Last, we provide an illustration of how such normative (albeit speaker-dependent) speed and velocity profiles would be instantiated via an interactive scenario that could be included within an extant computer-based speech therapy system. I will represent the classification accuracy results of kinematic data using HMM and SVM classification techniques. Advisors/Committee Members: Baljko, Melanie (advisor).

Subjects/Keywords: Speech therapy; Computer-based speech therapy; Consonant classification; Tongue tip trajectory; SVM classification; HMM classification; Speech data; Speed-based feature Derivation; Velocity-based feature derivation; Electromagnetic Articulography; Dynamic time warping; Plosive classification; Fricative classification

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zarringhalam, R. M. (2018). Consonant Classification Based on Tongue Tip Trajectories. (Masters Thesis). York University. Retrieved from http://hdl.handle.net/10315/34952

Chicago Manual of Style (16th Edition):

Zarringhalam, Rojin Majd. “Consonant Classification Based on Tongue Tip Trajectories.” 2018. Masters Thesis, York University. Accessed December 12, 2018. http://hdl.handle.net/10315/34952.

MLA Handbook (7th Edition):

Zarringhalam, Rojin Majd. “Consonant Classification Based on Tongue Tip Trajectories.” 2018. Web. 12 Dec 2018.

Vancouver:

Zarringhalam RM. Consonant Classification Based on Tongue Tip Trajectories. [Internet] [Masters thesis]. York University; 2018. [cited 2018 Dec 12]. Available from: http://hdl.handle.net/10315/34952.

Council of Science Editors:

Zarringhalam RM. Consonant Classification Based on Tongue Tip Trajectories. [Masters Thesis]. York University; 2018. Available from: http://hdl.handle.net/10315/34952

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