基于语音和文本的运动生成与匹配系统

Jonghyun Shin, Jun-Young Park, S. Kang
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引用次数: 0

摘要

基于语音和文本的运动生成在学术界和工业界都是一个新兴的研究领域。但有一个问题是,目前相关研究对生成运动结构的定义不同。为了解决这个问题,我们提出了一种新的系统来匹配生成的运动与SMPL-X。在本研究中,我们主要利用预训练模型中的关节信息,并将该模型与另一个具有不同关节结构的模型进行匹配。由于该系统运行在Unity平台上,因此可以应用于各个行业领域。详细的运动视频和代码可在https://github.com/kinsingo/Speech-and-Text-based-Motion-Generation-and-Matching-System
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speech and Text-Based Motion Generation and Matching System
Speech and text-based motion generation is an emerging research area in both academia and industry. However, there is a problem that related studies have defined the generated motion structure differently so far. To solve this problem, we propose a novel system for matching the generated motion to SMPL-X. In this study we focused on using joint information from a pre-trained model and matched this model to another model which has different joint structure. Since this system runs on Unity, it can be applied to various industry fields. Detailed motion videos and codes are available in https://github.com/kinsingo/Speech-and-Text-based-Motion-Generation-and-Matching-System
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