细分中的值如何影响线性模型的回归性能
Stephan R Kuberski1, Adamantios I Gafos1
1Department of Linguistics and Cognitive Sciences, University of Potsdam, Potsdam, Germanykuberski@uni-potsdam.de, gafos@uni-potsdam.de.
JASA express letters
|September 6, 2023
概括
这项研究揭示了运动细分值如何影响语音运动控制模型. 调整这些值会显著改变语音生成的动态模型性能.
科学领域:
- 语音运动控制器的控制器
- 生物力学 生物力学
- 动态系统建模动态系统建模
背景情况:
- 准确的语音制作模型需要将连续的语音细分为离散的运动.
- 目前的方法普遍使用基于速度的值来定义运动开始/结束.
- 门的选择会影响模型分析中使用的轨迹数据的数量.
研究的目的:
- 研究基于速度的值选择对语音运动细分的影响.
- 为了明确展示值选择如何调节动态语音模型的性能.
主要方法:
- 语音效应器运动轨迹的分析.
- 基于变速的值用于移动细分的应用.
- 使用细分移动数据对动态模型进行回归分析.
主要成果:
- 选择速度值直接影响用于分析的运动轨迹数据数量.
- 不同的值设置导致假设动态模型的回归性能具有可量化的变化.
- 这种调制突出了模型评估对细分参数的敏感性.
结论:
- 选择速度值是言语运动控制研究中的关键参数.
- 为了进行可靠的动态模型评估,需要明确考虑值效应.
- 未来的研究应该考虑细分选择对模型解释的影响.
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