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Performance Enhancement in Lip Synchronization Using MFCC Parameters

机译:使用MFCC参数增强嘴唇同步的性能

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Many multimedia applications and entertainment industry products like games, cartoons and film dubbing require speech driven face animation and audio-video synchronization. Only Automatic Speech Recognition system (ASR) does not give good results in noisy environment. Audio Visual Speech Recognition system plays vital role in such harsh environment as it uses both audio and visual information. In this paper, we have proposed a novel approach with enhanced performance over traditional methods that have been reported so far. Our algorithm works on the bases of acoustic and visual parameters to achieve better results. We have tested our system for English language using MFCC and LPC parameters of the speech. Lip parameters like lip width, lip height etc are extracted from the video and these both acoustic and visual parameters are used to train neural network. Our system is giving almost cent percent response against vowels.
机译:许多多媒体应用程序和娱乐行业产品(例如游戏,卡通和电影配音)都需要语音驱动的面部动画和音频视频同步。在嘈杂的环境中,只有自动语音识别系统(ASR)不能提供良好的结果。视听语音识别系统在恶劣的环境中起着至关重要的作用,因为它同时使用了视听信息。在本文中,我们提出了一种新颖的方法,该方法比迄今为止已报道的传统方法具有更高的性能。我们的算法基于声学和视觉参数来实现更好的结果。我们已经使用语音的MFCC和LPC参数对我们的系统进行了英语语言测试。从视频中提取诸如嘴唇宽度,嘴唇高度等嘴唇参数,并将这些声学和视觉参数用于训练神经网络。我们的系统针对元音给出了几乎百分之一的响应。

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