首页> 外文会议>ICONIP 2008;International conference on advances in neuro-information processing >Gabor Neural Network Based Facial Expression Recognition for Assistive Speech Expression
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Gabor Neural Network Based Facial Expression Recognition for Assistive Speech Expression

机译:基于Gabor神经网络的语音辅助表情识别。

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This research focuses on utilizing the biometrics recognition to trigger the speech expresser. Our selected biometric is facial expression. Though CPC have no verbal language ability, they have facial expression ability that can be interpreted to relate to their voice speech needs. However facial expression of a CPC may not be exactly identical at all times. Furthermore CPC are unique and require special speech profiles. After a thorough research in face recognition and artificial intelligence domain, neural network coupled with Gabor feature extraction is found to outperform others. A Neural Network with Gabor filters is built to train the facial expression classifiers. This research has proven successful to help CPC to express their voice speech through software with 98% successful facial recognition rate.
机译:这项研究的重点是利用生物识别技术来触发语音表达器。我们选择的生物特征是面部表情。尽管CPC没有口头语言能力,但他们具有可以被解释为与语音需求相关的面部表情能力。但是,每次点击费用的面部表情可能并非始终都是完全相同的。而且CPC是唯一的,需要特殊的语音配置文件。经过对人脸识别和人工智能领域的深入研究,发现神经网络与Gabor特征提取相结合的性能优于其他人。建立了带有Gabor过滤器的神经网络来训练面部表情分类器。事实证明,这项研究成功地帮助CPC通过软件以98%的面部识别成功率来表达他们的语音语音。

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