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首页> 外文会议>Annual conference of the International Speech Communication Association >A Case Study: Detecting Counselor Reflections in Psychotherapy for Addictions using Linguistic Features
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A Case Study: Detecting Counselor Reflections in Psychotherapy for Addictions using Linguistic Features

机译：案例研究：使用语言特征检测心理疗法对成瘾者的心理辅导

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Motivational Interviewing (MI) is a goal-oriented psychotherapy, employed in cases such as addiction, which helps clients (i.e., patients) explore and resolve their ambivalence about the problem at hand in a dialog setting. Measuring the counselor's proficiency with MI has typically been assessed via behavioral coding - a time consuming, non-technological approach. This paper examines a computational approach to assessing the quality of MI. Specifically, we focus on a particular aspect of the counselor behavior - reflections - believed to be a critical indicator of MI therapy quality. We automatically tag reflection instances in a maximum entropy Markov modeling framework using several linguistic features with rich contextual information obtained from the session transcripts. We achieve an F-score of over 80% while gaining insight about the information sources as perceived by the trained annotators.
机译：动机面试（MI）是一种面向目标的心理治疗方法，用于成瘾等情况，可帮助服务对象（即患者）在对话环境中探索并解决他们对当前问题的矛盾情绪。通常通过行为编码（一种耗时，非技术的方法）来评估咨询员对MI的熟练程度。本文研究了一种评估MI质量的计算方法。具体而言，我们专注于辅导员行为的一个特定方面-反思-被认为是MI治疗质量的关键指标。我们使用具有从会话成绩单获得的丰富上下文信息的几种语言功能，在最大熵马尔可夫建模框架中自动标记反射实例。我们获得了80％以上的F分数，同时获得了受过培训的注释者所感知的信息源的洞察力。

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