Identifying therapist conversational actions across diverse psychotherapeutic approaches
Identifying therapist conversational actions across diverse psychotherapeutic approaches
复制标题
识别不同心理治疗方法中治疗师的对话行为
DOI：
10.18653/v1/w19-3002
复制
发表时间：
2019
期刊：
影响因子：
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通讯作者：
K. McKeown
中科院分区：
文献类型：
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作者：
Fei;Derrick Hull;Jacob Levine;Bonnie Ray;K. McKeown
虽然治疗会话中的对话在主题和风格上都有很大的不同，但对治疗师使用的基本技术的理解可以为治疗师如何最好地帮助不同类型的客户提供有价值的见解。对话行为分类的目的是确定每个说话者在每句话中所采取的会话“行为”，如同情、解决问题或检查假设。我们建议将对话行为分类应用于治疗成绩单，使用治疗特定的标签计划，以获得高层次的理解治疗会话中的会话流。我们提出了一种新的注释方案，跨越多种心理治疗方法，将其应用到一个大型的和多样化的语料库的心理治疗成绩单，并提出和讨论分类结果使用SVM和基于神经网络的模型。结果表明，确定的结构和流程的治疗行动是一个可实现的目标，开辟了机会，在未来提供治疗建议，针对特定的客户端的情况。
While conversation in therapy sessions can vary widely in both topic and style, an understanding of the underlying techniques used by therapists can provide valuable insights into how therapists best help clients of different types. Dialogue act classification aims to identify the conversational “action” each speaker takes at each utterance, such as sympathizing, problem-solving or assumption checking. We propose to apply dialogue act classification to therapy transcripts, using a therapy-specific labeling scheme, in order to gain a high-level understanding of the flow of conversation in therapy sessions. We present a novel annotation scheme that spans multiple psychotherapeutic approaches, apply it to a large and diverse corpus of psychotherapy transcripts, and present and discuss classification results obtained using both SVM and neural network-based models. The results indicate that identifying the structure and flow of therapeutic actions is an obtainable goal, opening up the opportunity in the future to provide therapeutic recommendations tailored to specific client situations.