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Using physiology and language cues for modeling verbal response latencies of children with ASD
Abstract
Signal-derived measures can provide effective ways towards quantifying human behavior. Verbal Response Latencies (VRLs) of children with Autism Spectrum Disorders (ASD) during conversational interactions are able to convey valuable information about their cognitive and social skills. Motivated by the inherent gap between the external behavior and inner affective state of children with ASD, we study their VRLs in relation to their explicit but also implicit behavioral cues. Explicit cues include the children's language use, while implicit cues are based on physiological signals. Using these cues, we perform classification and regression tasks to predict the duration type (short/long) and value of VRLs of children with ASD while they interacted with an Embodied Conversational Agent (ECA) and their parents. Since parents are active participants in these triadic interactions, we also take into account their linguistic and physiological behaviors. Our results suggest an association between VRLs and these externalized and internalized signal information streams, providing complementary views of the same problem.
Figures
(a) Gamma/Exponential VRL distributions with parameters computed using Maximum Likelihood Estimation (MLE) for subjects with PDD and Autism. (b) Distribution of mean EDA during VRL instances for subjects with PDD and Autism.
(a) Gamma/Exponential VRL distributions with parameters computed using Maximum Likelihood Estimation (MLE) for subjects with PDD and Autism. (b) Distribution of mean EDA during VRL instances for subjects with PDD and Autism.
Keywords
Verbal response latency | Electrodermal Activity | Language modeling | Autism Spectrum Disorders | Generalized linear regression
Authors
Publication Date
2013/05/26
Conference
IEEE International Conference on Acoustics, Speech and Signal Processing
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
DOI
10.1109/icassp.2013.6638349
Publisher
IEEE