Audio to visual signal mappings with HMM

WenTao Liu, Baocai Yin, XiBin Jia, Dehui Kong

Abstract: There has been a large amount of research on speech driven face animation. Particularly, recently research efforts have been demonstrated that the hidden Markov model techniques could achieve a high level of success in the field of audio/visual mapping without language information. In this paper, firstly a linear model based facial representation method was applied, which extracts face features as a global feature. Secondly, a HMM based method was presented, which includes a two-level frame to promote the audio-visual mapping result.