Predicting pragmatic discourse features in the language of adults with autism spectrum disorder

Christine Yang, Duanchen Liu, Qingyun Yang, Zoey Liu, Emily Prud’hommeaux


Abstract
Individuals with autism spectrum disorder (ASD) experience difficulties in social aspects of communication, but the linguistic characteristics associated with deficits in discourse and pragmatic expression are often difficult to precisely identify and quantify. We are currently collecting a corpus of transcribed natural conversations produced in an experimental setting in which participants with and without ASD complete a number of collaborative tasks with their neurotypical peers. Using this dyadic conversational data, we investigate three pragmatic features – politeness, uncertainty, and informativeness – and present a dataset of utterances annotated for each of these features on a three-point scale. We then introduce ongoing work in developing and training neural models to automatically predict these features, with the goal of identifying the same between-groups differences that are observed using manual annotations. We find the best performing model for all three features is a feed-forward neural network trained with BERT embeddings. Our models yield higher accuracy than ones used in previous approaches for deriving these features, with F1 exceeding 0.82 for all three pragmatic features.
Anthology ID:
2021.acl-srw.29
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
284–291
Language:
URL:
https://aclanthology.org/2021.acl-srw.29
DOI:
10.18653/v1/2021.acl-srw.29
Bibkey:
Cite (ACL):
Christine Yang, Duanchen Liu, Qingyun Yang, Zoey Liu, and Emily Prud’hommeaux. 2021. Predicting pragmatic discourse features in the language of adults with autism spectrum disorder. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop, pages 284–291, Online. Association for Computational Linguistics.
Cite (Informal):
Predicting pragmatic discourse features in the language of adults with autism spectrum disorder (Yang et al., ACL-IJCNLP 2021)
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PDF:
https://aclanthology.org/2021.acl-srw.29.pdf
Video:
 https://aclanthology.org/2021.acl-srw.29.mp4