Juhi Pandey


2022

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Identifying stable speech-language markers of autism in children: Preliminary evidence from a longitudinal telephony-based study
Sunghye Cho | Riccardo Fusaroli | Maggie Rose Pelella | Kimberly Tena | Azia Knox | Aili Hauptmann | Maxine Covello | Alison Russell | Judith Miller | Alison Hulink | Jennifer Uzokwe | Kevin Walker | James Fiumara | Juhi Pandey | Christopher Chatham | Christopher Cieri | Robert Schultz | Mark Liberman | Julia Parish-morris
Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology

This study examined differences in linguistic features produced by autistic and neurotypical (NT) children during brief picture descriptions, and assessed feature stability over time. Weekly speech samples from well-characterized participants were collected using a telephony system designed to improve access for geographically isolated and historically marginalized communities. Results showed stable group differences in certain acoustic features, some of which may potentially serve as key outcome measures in future treatment studies. These results highlight the importance of eliciting semi-structured speech samples in a variety of contexts over time, and adds to a growing body of research showing that fine-grained naturalistic communication features hold promise for intervention research.

2018

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Oral-Motor and Lexical Diversity During Naturalistic Conversations in Adults with Autism Spectrum Disorder
Julia Parish-Morris | Evangelos Sariyanidi | Casey Zampella | G. Keith Bartley | Emily Ferguson | Ashley A. Pallathra | Leila Bateman | Samantha Plate | Meredith Cola | Juhi Pandey | Edward S. Brodkin | Robert T. Schultz | Birkan Tunç
Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impaired social communication and the presence of restricted, repetitive patterns of behaviors and interests. Prior research suggests that restricted patterns of behavior in ASD may be cross-domain phenomena that are evident in a variety of modalities. Computational studies of language in ASD provide support for the existence of an underlying dimension of restriction that emerges during a conversation. Similar evidence exists for restricted patterns of facial movement. Using tools from computational linguistics, computer vision, and information theory, this study tests whether cognitive-motor restriction can be detected across multiple behavioral domains in adults with ASD during a naturalistic conversation. Our methods identify restricted behavioral patterns, as measured by entropy in word use and mouth movement. Results suggest that adults with ASD produce significantly less diverse mouth movements and words than neurotypical adults, with an increased reliance on repeated patterns in both domains. The diversity values of the two domains are not significantly correlated, suggesting that they provide complementary information.