In　this　paper,　we　propose　a　codebook-based　speech　enhancement　scheme　under　a　novel　Bayesian　framework.　The　goal　of　this　framework　is　to　optimally　combine　power　spectral　envelopes　(PSEs)　estimation　of　speech　and　noise　from　speech　absence　hypothesis　and　speech　presence　hypothesis　in　current　frame.　Then,　the　noisy　observation　is　passed　through　the　reconstructed　Wiener　filter　to　obtain　the　enhanced　amplitude　spectrum.　In　order　to　further　improve　the　speech　quality,　we　exploit　one　geometric　equation　to　derive　the　phase　spectrum　of　the　clean　speech.　Finally,　both　enhanced　amplitude　and　estimated　phase　spectra　are　used　for　recovering　the　clean　speech　signal.　Experiments　show　that　the　proposed　approach　generates　considerable　improvement　compared　to　the　conventional　codebook-based　methods.