从以任务为导向和开放领域的人机对话中预测人格.
Ao Guo1, Ryu Hirai2, Atsumoto Ohashi2
1Graduate School of Informatics, Nagoya University, Nagoya, Japan. guo.ao.i6@f.mail.nagoya-u.ac.jp.
Scientific reports
|February 17, 2024
概括
对话系统可以从对话中预测用户的个性特征. 开放领域的对话系统比以任务为导向的系统更准确地预测人格,尽管外向在两种系统中都是可预测的.
科学领域:
- 自然语言处理自然语言处理.
- 人与计算机的交互
- 计算语言学 计算语言学
背景情况:
- 对话系统旨在适应用户的个性,以改善互动.
- 之前的研究探讨了在端到端系统中使用MBTI特征进行人格预测.
- 人格预测在不同对话系统和特征中的通用性仍然不清楚.
研究的目的:
- 从各种系统类型和个性框架的对话中调查个性特征预测的可行性.
- 为了比较开放域与以任务为导向的对话系统在人格预测方面的有效性.
- 分析对话特征对预测准确性的影响.
主要方法:
- 招募了378名参与者进行人格调查问卷和以任务为导向的对话 (管道和端到端系统).
- 在开放领域对话系统中吸引了186名额外的参与者.
- 开发基于BERT的模型,从收集的对话数据中预测人格特征.
主要成果:
- 与以任务为导向的系统相比,开放域对话系统的整体人格预测准确度更高.
- 外向 (五大特征) 在开放域和管道任务导向对话中同样可预测.
- 在面向任务的对话数据上训练的模型无法预测开放域对话的特征,反之亦然.
结论:
- 对话系统类型显著影响人格预测的准确性.
- 开放领域的对话为广泛的个性特征预测提供了更有前途的途径.
- 未来的研究应该考虑对话背景,系统类型和特定的人格特征,以有效预测.
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