Automatic gesture generation from speech generally relies on implicit modelling of the nondeterministic speech-gesture relationship and can result in averaged motion lacking defined form. Here, we propose a database-driven approach of selecting gestures based on specific motion characteristics that have been shown to be associated with the speech audio. We extend previous work that identified expressive parameters of gesture motion that can both be predicted from speech and are perceptually important for a good speech-gesture match, such as gesture velocity and finger extension. A perceptual study was performed to evaluate the appropriateness of the gestures selected with our method. We compare our method with two baseline selection methods. The first respects timing, the desired onset and duration of a gesture, but does not match gesture form in other ways. The second baseline additionally disregards the original gesture timing for selecting gestures. The gesture sequences from our method were rated as a significantly better match to the speech than gestures selected by either baseline method.

中文翻译：

---

这是一场比赛！使用表达性参数匹配的手势生成

从语音自动生成手势通常依赖于不确定性语音-手势关系的隐式建模，并且可能导致平均运动缺少定义的形式。在这里，我们提出了一种数据库驱动的方法，该方法基于已显示与语音音频相关联的特定运动特征来选择手势。我们扩展了以前的工作，这些工作确定了可以从语音中预测出的手势动作的表达参数，这些参数对于良好的语音手势匹配在感知上很重要，例如手势速度和手指伸展。进行了一项感知研究，以评估使用我们的方法选择的手势的适当性。我们将我们的方法与两种基线选择方法进行了比较。首先要考虑时间，手势的期望开始时间和持续时间，但在其他方面与手势形式不匹配。第二基线另外忽略了用于选择手势的原始手势时序。与任何一种基线方法选择的手势相比，我们方法中的手势序列被认为与语音的匹配性更好。