Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios

Zhuohao Chen, Nikolaos Flemotomos, Zac Imel, David Atkins, Shrikanth Narayanan


Abstract
In psychotherapy interactions, the quality of a session is assessed by codifying the communicative behaviors of participants during the conversation through manual observation and annotation. Developing computational approaches for automated behavioral coding can reduce the burden on human coders and facilitate the objective evaluation of the intervention. In the real world, however, implementing such algorithms is associated with data sparsity challenges since privacy concerns lead to limited available in-domain data. In this paper, we leverage a publicly available conversation-based dataset and transfer knowledge to the low-resource behavioral coding task by performing an intermediate language model training via meta-learning. We introduce a task augmentation method to produce a large number of “analogy tasks” — tasks similar to the target one — and demonstrate that the proposed framework predicts target behaviors more accurately than all the other baseline models.
Anthology ID:
2022.findings-emnlp.425
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2022
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5787–5795
Language:
URL:
https://aclanthology.org/2022.findings-emnlp.425
DOI:
10.18653/v1/2022.findings-emnlp.425
Bibkey:
Cite (ACL):
Zhuohao Chen, Nikolaos Flemotomos, Zac Imel, David Atkins, and Shrikanth Narayanan. 2022. Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 5787–5795, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios (Chen et al., Findings 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.findings-emnlp.425.pdf