By Selma Yilmazyildiz, Wesley Mattheyses (auth.), Yueting Zhuang, Shi-Qiang Yang, Yong Rui, Qinming He (eds.)
Welcome to the court cases of the seventh Paci?c-Rim convention on Multimedia (PCM2006)heldatZhejiang University,Hangzhou,China,November2-4,2006. Following the good fortune of the former meetings, PCM 2000 in Sydney, PCM 2001 in Beijing, PCM 2002 in Hsinchu, PCM 2003 in Singapore, PCM 2004 in Tokyo, and PCM 2005 in Jeju, PCM 2006 back introduced jointly researchers, builders, practitioners, and educators within the ?eld of multimedia from around the globe. either theoretical breakthroughs and useful platforms have been provided on the convention. there have been periods from multimedia retrieval to multimedia coding to multimedia security,coveringa huge spectrum of multimedia examine. PCM2006featuredacomprehensiveprogramincludingkeynotetalks,regular paper shows, and distinctive classes. We acquired 755 submissions and the quantity used to be the biggest between all of the PCMs. From this type of huge variety of submissions,weacceptedonly116oralpresentations.Wekindlyacknowledgethe nice aid supplied by means of this system Committee participants within the reviewing of submissions, in addition to the extra reviewers who generously spent many hours. the various worthwhile reviews supplied by means of the reviewing technique are very priceless to authors’ present and destiny research.
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Additional info for Advances in Multimedia Information Processing - PCM 2006: 7th Pacific Rim Conference on Multimedia, Hangzhou, China, November 2-4, 2006. Proceedings
Multimodality in language and speech systems. B. Granström, D. House and I. Karlsson. Dordrecht, The Netherlands, Kluwer Academic: 173–207. 28. -M. Eigsti, S. Yano and K. G. Munhall (1998). ” Perception & Psychophysics 60: 926940. 29. Xu, Y. and M. M. Chun (2006). ” Nature 440: 91-95. 30. Yarbus, A. L. (1967). Eye movements during perception of complex objects. Eye Movements and Vision'. L. A. Riggs. New York, Plenum Press. VII: 171-196. R. be Abstract. We present an audio-visual automatic speech recognition system, which signiﬁcantly improves speech recognition performance over a wide range of acoustic noise levels, as well as under clean audio conditions.
20. Premack, D. and G. Woodruff (1978). ” Behavioral and brain sciences 1: 515-526. 21. , G. Bailly and F. Elisei (2006). Does a virtual talking face generate proper multimodal cues to draw user's attention towards interest points? Language Ressources and Evaluation Conference (LREC), Genova - Italy: 2544-2549. 22. , F. Davide and W. A. IJsselsteijn (2003). Being there: concepts, effects and measurements of user presence in synthetic environments. Amsterdam, IOS Press. 23. Scassellati, B. (2001).
19–30, 2006. c Springer-Verlag Berlin Heidelberg 2006 20 I. Ravyse et al. have superior recognition accuracy, especially in noisy conditions [4,5,6]. The use of visual features in audio-visual speech recognition is motivated by the speech formation mechanism and the natural speech ability of humans to reduce audio ambiguities using visual cues. Moreover, the visual information provides complementary cues that cannot be corrupted by the acoustic noise of the environment. However, problems such as the selection of the optimal set of visual features, and the optimal models for audio-visual integration remain challenging research topics.