基于高斯混合模型(GMM)的视听发音反演

I. Ozbek, M. Demirekler
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引用次数: 0

摘要

在这项研究中,我们研究了基于高斯混合模型(GMM)的视听信息的发音反转。在这种方法中,发音运动和音频(和/或视觉)数据的联合分布通过混合高斯分布进行建模。GMM的条件期望值被用作音频(和/或视觉)和听觉空间之间的回归函数。我们还研究了各种融合方法,以便在关节倒置中结合声学和视觉信息。融合方法提高了关节内翻的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Audiovisual articulatory inversion based on Gaussian Mixture Model (GMM)
In this study, we examined articulatory inversion using audiovisual information based on Gaussian Mixture Model (GMM). In this method the joint distribution of the articulatory movement and audio (and/or visual) data are modelled via a mixture of Gaussians. The conditional expected value of the GMM is used as regression function between the audio (and/orvisual) and ar-ticulatory spaces. We also examined various fusion methods in order to combine acoustic and visual information in articula-tory inversion. The fusion methods improve the performance of articulatory inversion.
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