姿态增强:以正确的方式镜像

John T. Windle, Sarah Taylor, David Greenwood, Iain Matthews
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引用次数: 1

摘要

我们展示了一种有效的增强语音动画数据的方法,并显示出可将真实数据量增加一倍的相当性能。我们研究了横向镜像作为数据增强的一种手段,在多说话,语音到运动建模的3D姿势的影响。我们的方法使用双向LSTM从使用问题无关语音编码器(PASE+)提取的音频特征中生成3D关节位置[7]。我们证明了用于增强的朴素镜像对模型性能有不利影响。我们展示了我们提供虚拟说话人身份嵌入的方法比没有增强的方法提高了性能,并且与在相同数量的真实数据样本上训练的模型相竞争。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pose augmentation: mirror the right way
We demonstrate an effective method of augmenting speech animation data, and show comparable performance to double the quantity of real data. We investigate the effect of lateral mirroring as a means of data augmentation for 3D poses in multi-speaker, speech-to-motion modelling. Our approach uses a bi-directional LSTM to generate 3D joint positions from audio features extracted using problem-agnostic speech encoder (PASE+) [7]. We demonstrate that naive mirroring for augmentation has a detrimental effect on model performance. We show our method of providing a virtual speaker identity embedding improved performance over no augmentation and was competitive with a model trained on an equal number of samples of real data.
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