演讲焦虑的实时预测模型

Everlyne Kimani, T. Bickmore, Rosalind W. Picard, Matthew Goodwin, H. Jimison
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引用次数: 0

摘要

口头表达能力对大多数人的学术和职业发展至关重要。然而,由于公众演讲焦虑,许多人发现口头演讲具有挑战性,并经常避免它们,从而损害他们的职业生涯。公共演讲焦虑干预可以帮助演讲者在演讲过程中控制他们的焦虑,这可以帮助许多演讲者。在本文中,我们提出了一个模型,用于评估演讲期间的公共演讲焦虑,这是开发实时焦虑干预的第一步。我们提出了地面真实数据收集的方法,以及使用音频数据进行实时焦虑检测的神经网络模型的结果。我们的研究结果表明,使用LSTM模型,我们可以预测演讲过程中演讲焦虑的时刻。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time Public Speaking Anxiety Prediction Model for Oral Presentations
Oral presentation skills are essential for most people’s academic and career development. However, due to public speaking anxiety, many people find oral presentations challenging and often avoid them to the detriment of their careers. Public speaking anxiety interventions that help presenters manage their anxiety as it occurs during a presentation can help many presenters. In this paper, we present a model for assessing public speaking anxiety during a presentation—a first step towards developing real-time anxiety interventions. We present our method for ground truth data collection and the results of neural network models for real-time anxiety detection using audio data. Our results show that using an LSTM model we can predict moments of speaking anxiety during a presentation.
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