Title :
Automatic visual speech segmentation
Author :
Talea, Hamed ; Yaghmaie, Khashayar
Author_Institution :
Dept. of Electr. & Comput. Eng., Semnan Univ., Semnan, Iran
Abstract :
Speech recognition techniques which rely on audio features of speech degrade in performance in noisy environments. Visual Speech Recognition helps this by incorporating a visual signal into the recognition process. The performance of automatic speech recognition (ASR) system can be significantly enhanced with additional information from visual speech elements such as the movement of lips, tongue, and teeth. This paper introduces a combined method for lip region extraction and mouth area estimation, which is then used to develop technique for automatic visual speech segmentation. The accuracy of this method is verified by applying it for syllable boundary separation and the following vowel segmentation in multi syllable words and phrases.
Keywords :
feature extraction; speech recognition; audio features; automatic speech recognition; automatic visual speech segmentation; lip region extraction; mouth area estimation; speech recognition; visual signal; Image segmentation; Noise measurement; Speech; Lip tracking; Speech segmentation; lipreading; visual feature; visual syllable separation;
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
DOI :
10.1109/ICCSN.2011.6014877