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

• URL: http://arxiv.org/abs/2210.14254v1
• Date: Tue, 25 Oct 2022 18:15:25 GMT
• Title: Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios
• Authors: Zhuohao Chen, Nikolaos Flemotomos, Zac E. Imel, David C. Atkins, Shrikanth Narayanan
• Abstract summary: In psychotherapy interactions, the quality of a session is assessed by codifying the communicative behaviors of participants during the conversation. In this paper, we leverage a publicly available conversation-based dataset and transfer knowledge to the low-resource behavioral coding task. 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.
• Score: 35.44178630251169
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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