Deep Lip Reading - A Deep Learning Based Lip-Reading Software for the Hearing Impaired

被引:0
|
作者
Abrar, Mohammed Abid [1 ]
Islam, A. N. M. Nafiul [1 ]
Hassan, Mohammad Muntasir [1 ]
Islam, Mohammad Tariqul [1 ]
Shahnaz, Celia [1 ]
Fattah, Shaikh Anowarul [1 ]
机构
[1] BUET, Dept EEE, Dhaka 1205, Bangladesh
关键词
Visual Speech Recognition; Lip reading; Deep Learning;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Lip reading is the task of decoding and understanding speech from the movement of a speaker's mouth. This can be extremely beneficial for aiding the hearing impaired to 'listen' to people who do not know sign language in real-world environments with a lot of noise pollution. Orthodoxically methods have focused mainly on heavy preprocessing. Despite showing tremendous potential, application of deep learning algorithms has been limited in this field. Here we present a convolutional neural network model to predict words from videos without any audio. It is developed using the pre-trained deep learning architecture VGG Net, pre -trained on the ImageNet Database with some custom modifications on the MIRACL-VC1 Dataset of 10 words. The model achieved an accuracy of 94.86% in training, 93.82% in validation and 60% in testing. An app has been developed using this model which can use cloud computing to run the model real time in any smartphone to aid the hearing-impaired in their day-to-day activities and can make conversations with hearing impaired people more natural, organic as well as cost friendly.
引用
收藏
页码:40 / 44
页数:5
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