Classifying language-related developmental disorders from speech cues: The promise and the potential confounds
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 long-term 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 template-based prosodic and formant modeling as well as goodness of pronunciation modeling, reporting above chance classification accuracies. Copyright © 2013 ISCA.
