Learning one-to-many mapping functions for audio-visual integrated perception
Jung-Hui Lim, Dokwan Oh, Soo-Young Lee · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
In noisy environment the human speech perception utilizes visual lip-reading as well as audio phonetic classification. This audio-visual integration may be done by combining the two sensory features at the early stage. Also, the top-down attention may integrate the two modalities. For the sensory feature fusion we introduce mapping functions between the audio and visual manifolds. Especially, we present an algorithm to provide one-to-many mapping function for the videoto- audio mapping. The top-down attention is also presented to integrate both the sensory features and classification results of both modalities, which is able to explain McGurk effect. Each classifier is separately implemented by the Hidden-Markov Model (HMM), but the two classifiers are combined at the top level and interact by the top-down attention.