@inproceedings{cho-etal-2022-identifying,
title = "Identifying stable speech-language markers of autism in children: Preliminary evidence from a longitudinal telephony-based study",
author = "Cho, Sunghye and
Fusaroli, Riccardo and
Pelella, Maggie Rose and
Tena, Kimberly and
Knox, Azia and
Hauptmann, Aili and
Covello, Maxine and
Russell, Alison and
Miller, Judith and
Hulink, Alison and
Uzokwe, Jennifer and
Walker, Kevin and
Fiumara, James and
Pandey, Juhi and
Chatham, Christopher and
Cieri, Christopher and
Schultz, Robert and
Liberman, Mark and
Parish-morris, Julia",
editor = "Zirikly, Ayah and
Atzil-Slonim, Dana and
Liakata, Maria and
Bedrick, Steven and
Desmet, Bart and
Ireland, Molly and
Lee, Andrew and
MacAvaney, Sean and
Purver, Matthew and
Resnik, Rebecca and
Yates, Andrew",
booktitle = "Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology",
month = jul,
year = "2022",
address = "Seattle, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.clpsych-1.4",
doi = "10.18653/v1/2022.clpsych-1.4",
pages = "40--46",
abstract = "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.",
}
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<abstract>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.</abstract>
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%0 Conference Proceedings
%T Identifying stable speech-language markers of autism in children: Preliminary evidence from a longitudinal telephony-based study
%A Cho, Sunghye
%A Fusaroli, Riccardo
%A Pelella, Maggie Rose
%A Tena, Kimberly
%A Knox, Azia
%A Hauptmann, Aili
%A Covello, Maxine
%A Russell, Alison
%A Miller, Judith
%A Hulink, Alison
%A Uzokwe, Jennifer
%A Walker, Kevin
%A Fiumara, James
%A Pandey, Juhi
%A Chatham, Christopher
%A Cieri, Christopher
%A Schultz, Robert
%A Liberman, Mark
%A Parish-morris, Julia
%Y Zirikly, Ayah
%Y Atzil-Slonim, Dana
%Y Liakata, Maria
%Y Bedrick, Steven
%Y Desmet, Bart
%Y Ireland, Molly
%Y Lee, Andrew
%Y MacAvaney, Sean
%Y Purver, Matthew
%Y Resnik, Rebecca
%Y Yates, Andrew
%S Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, USA
%F cho-etal-2022-identifying
%X 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.
%R 10.18653/v1/2022.clpsych-1.4
%U https://aclanthology.org/2022.clpsych-1.4
%U https://doi.org/10.18653/v1/2022.clpsych-1.4
%P 40-46
Markdown (Informal)
[Identifying stable speech-language markers of autism in children: Preliminary evidence from a longitudinal telephony-based study](https://aclanthology.org/2022.clpsych-1.4) (Cho et al., CLPsych 2022)
ACL
- 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, and Julia Parish-morris. 2022. Identifying stable speech-language markers of autism in children: Preliminary evidence from a longitudinal telephony-based study. In Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology, pages 40–46, Seattle, USA. Association for Computational Linguistics.