自动对口型及其在移动设备新多媒体服务中的应用

G. Zoric, I. Pandzic
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引用次数: 7

摘要

本文提出了一种将自然语音实时映射到唇形动画的新方法。用MFCC向量表示语音信号,利用神经网络对语音信号进行分类。神经网络的拓扑结构采用遗传算法自动配置。这消除了繁琐的人工神经网络设计的需要,并大大提高了viseme分类结果。该方法具有实时和离线两种模式,适用于各种应用。因此,我们提出了基于上述对口型系统的移动设备多媒体服务。
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Automatic lip sync and its use in the new multimedia services for mobile devices
In this paper we present a new method for mapping natural speech to lip shape animation in real time. The speech signal, represented by MFCC vectors, is classified into viseme classes using neural networks. The topology of neural networks is automatically configured using genetic algorithms. This eliminates the need for tedious manual neural network design by trial and error and considerably improves the viseme classification results. This method is available in real-time and offline mode, and is suitable for various applications. So, we propose the new multimedia services for mobile devices based on the lip sync system described.
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