Design of tool for analysis of speech development disorders using landmarks and other acoustic cues
Name
1016159223-MIT.pdf
Description
Full printable version
Size
6.38 MB
Format
Adobe PDF
Checksum (MD5)
06fa4f109d2e4152a2e6d7304eab2e1c
Author(s)
Talkar, Tanya
Advisor(s)
Stefanie Shattuck-Hufnagel and Jeung-Yoon Elizabeth Choi.
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
Non-word repetition tasks have been used to diagnose children with various developmental difficulties with phonology, but these productions have not been phonetically analyzed to reveal the nature of the modifications produced by children diagnosed with SLI, autism spectrum disorder or dyslexia compared to those produced by typically-developing children. In this thesis, we compared the modification of predicted acoustic cues to distinctive features of manner, place and voicing for just under 30 children (ages 5-12), for the CN-Rep word inventory, in an extension of the earlier analysis in Levy et al. 2014. Feature cues, including abrupt acoustic landmarks (Stevens 2002) and other acoustic feature cues, were hand-labeled and analysis of factors that may influence feature cue modifications included position in the word, position in the syllable, word length measured in syllables, lexical stress, and manner type. Results suggest specific patterns of modification in specific contexts for specific clinical populations. These findings set the foundation for understanding how phonetic variation in speech arises in both typical and clinical populations, and for using this knowledge to develop tools to aid in more accurate and insightful diagnosis as well as improved intervention methods.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 71).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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