This　paper　aims　to　give　a　solutions　for　the　construction　of　chinese　visual　speech　feature　model　based　on　HMM.　We　propose　and　discuss　three　kind　representation　model　of　the　visual　speech　which　are　lip　geometrical　features,　lip　motion　features　and　lip　texture　features.　The　model　combines　the　advantages　of　the　local　LBP　and　global　DCT　texture　information　together,　which　shows　better　performance　than　the　single　feature.　Equally　the　model　combines　the　advantages　of　the　local　LBP　and　geometrical　information　together　is　better　than　single　feature.　By　computing　the　recognition　rate　of　the　visemes　from　the　model,　the　paper　shows　the　HMM　which　describing　the　dynamic　of　speech,　coupled　with　the　combined　feature　for　describing　the　global　and　local　texture　is　the　best　model.　©　(2012)　Trans　Tech　Publications,　Switzerland.