论文标题
心理治疗课程的神经主题建模
Neural Topic Modeling of Psychotherapy Sessions
论文作者
论文摘要
在这项工作中，我们比较了从心理治疗会话中从语音记录中解析的心理治疗会话的不同精神病疾病的局部倾向时进行比较。我们还结合了时间建模，将这种额外的解释性放在行动中，通过将主题相似性解析为转向级别分辨率的时间序列。我们认为，这个主题建模框架可以为治疗师提供可解释的见解，以最佳地决定其策略并提高心理治疗效果。
In this work, we compare different neural topic modeling methods in learning the topical propensities of different psychiatric conditions from the psychotherapy session transcripts parsed from speech recordings. We also incorporate temporal modeling to put this additional interpretability to action by parsing out topic similarities as a time series in a turn-level resolution. We believe this topic modeling framework can offer interpretable insights for the therapist to optimally decide his or her strategy and improve psychotherapy effectiveness.
