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Realistic facial animation of speech synchronization for Indonesian language

机译:印尼语语音同步的逼真的面部动画

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Speech synchronization is one of the studies in the field of facial animation that has been widely studied, which results in speech animation, but there are still many challenges that have not been reached at this time, one of which is realistic speech synchronization. Because of differences in visual phoneme (viseme) in the pronunciation of each language, it is very difficult to make speech synchronization tools that are applicable for all languages, and at present there are no speech synchronization tools that can provide good results for Indonesian Language. This study proposes the introduction of co-articulation in speech synchronization to produce a more realistic animation, and viseme mapping based on the consonant-vowel (CV) syllable pattern in the Indonesian language, resulting in a more specific viseme group, so it supports the development of realistic speech synchronization, next called as Bahasa Speech Sync. Co-articulation calculation is done using Kochanek-Bartels spline interpolation approach which adds tension, bias and continuity parameters, using the 4 control points taken from real human videos, to accommodate the concept of co-articulation. Viseme mapping is done by comparing the difference in distance between the 12 crucial points with a point of reference for each syllable. Based on the results of our proposed viseme grouping procedure, we have simplified the viseme generation from a combination of 21 consonants and 5 vowels into 24 groups of viseme, 18 of which represent the start position while 6 groups represent the and position. Test result of the similarity of the movement between generated animation and real human videos has achieved 89% “realistic” perception based on our proposed distance criteria.
机译:语音同步是面部动画领域中已被广泛研究的一项研究,其产生了语音动画,但是目前还没有实现许多挑战,其中之一是逼真的语音同步。由于每种语言的发音在语音音素(viseme)方面存在差异,因此很难制作适用于所有语言的语音同步工具,并且目前还没有能够为印尼语提供良好效果的语音同步工具。本研究建议在语音同步中引入共发音以产生更逼真的动画,并基于印尼语中的辅音元音(CV)音节模式进行视位映射,从而形成更具体的视位组,因此它支持开发逼真的语音同步,接下来称为Bahasa语音同步。使用Kochanek-Bartels样条插值方法进行协同发音计算,该方法通过使用从真实人类视频中获取的4个控制点来增加张力,偏差和连续性参数,以适应协同发音的概念。通过比较12个关键点之间的距离差异与每个音节的参考点来完成Viseme映射。根据我们提出的视位素分组过程的结果,我们将视位素的生成简化了,将21个辅音和5个元音组合成24组视位素,其中18个代表起始位置,而6个组代表和位。根据我们提出的距离标准,所生成的动画与真实人类视频之间的运动相似性的测试结果已实现89%的“真实”感知。

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