14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Classifying Language-Related Developmental Disorders from Speech Cues: The Promise and the Potential Confounds

Daniel Bone, Theodora Chaspari, Kartik Audkhasi, James Gibson, Andreas Tsiartas, Maarten Van Segbroeck, Ming Li, Sungbok Lee, Shrikanth Narayanan

University of Southern California, USA

Speech and spoken language cues offer a valuable means to measure and model human behavior. Computational models of speech behavior have the potential to support health care through assistive technologies, informed intervention, and efficient longterm monitoring. The Interspeech 2013 Autism Sub-Challenge addresses two developmental disorders that manifest in speech: autism spectrum disorders and specific language impairment. We present classification results with an analysis on the development set including a discussion of potential confounds in the data such as recording condition differences. We hence propose study of features within these domains that may inform realistic separability between groups as well as have the potential to be used for behavioral intervention and monitoring. We investigate templatebased prosodic and formant modeling as well as goodness of pronunciation modeling, reporting above chance classification accuracies.

Full Paper

Bibliographic reference.  Bone, Daniel / Chaspari, Theodora / Audkhasi, Kartik / Gibson, James / Tsiartas, Andreas / Segbroeck, Maarten Van / Li, Ming / Lee, Sungbok / Narayanan, Shrikanth (2013): "Classifying language-related developmental disorders from speech cues: the promise and the potential confounds", In INTERSPEECH-2013, 182-186.