![]() ![]() The system depends mainly on recognizing the speaker using the visual speech signal alone. This paper presents a visual passwords system to increase security. The experimental results show the average accuracy about 86.8% in recognition 31 Persian words. After obtaining features from the videos an artificial neural network has been employed as classifier. Five speaker, three men and two women, have participated for capturing the videos of the spoken words. ![]() To improve the system performance visual word has been used as the shortest element of visual speech. The method is based on the fast furrier transform combined with the color specification of the frames in the recorded video of the spoken word. In this study a new method has been proposed for extracting features from a video containing a certain Persian words without any audio signal. However, similar to speech recognition, lipreading systems also face several challenges due to variances in the inputs, such as with facial features, skin colors, speaking speeds, and intensities. Automatic lipreading plays an important role in human computer interaction in noisy environments where audio speech recognition may be difficult. ![]()
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March 2023
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