الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Multimodal speech recognition is proved to be one of the most
promising solutions for robust speech recognition, especially when
the acoustic signal is corrupted by noise. The visual signal can be
used to obtain more information to enhance the speech recognition
accuracy in noisy system because it is not affected by the acoustic
noise. In the situations when the SNR of acoustic signals is low, the
video cues can compensate the acoustic signals, and thus their
method significantly improve the recognition accuracy.
The critical stage in designing robust speech recognition system is
the choice of reliable classification method from large variety of the
existing classification techniques. This research introduces an
Audio-Visual Speech Recognition (AVSR) model using both audio
and visual speech modality to improve recognition accuracy in a
clean and noisy environment.