In　this　paper,　we　propose　a　speech　enhancement　method　based　on　a　few　shapes　of　speech　spectrum.　First,　we　utilizes　Minima　Controlled　Recursive　Averaging　(MCRA)　algorithm　to　estimate　the　noise　instead　of　training　the　noise　codebooks　used　in　conventional　method.　Then,　the　spectral　shapes　and　the　spectral　gains　of　speech　and　noise　are　optimized　by　minimizing　the　spectral　distortion　between　the　noisy　speech　and　the　combination　of　noise　and　speech.　Next,　the　normalized　cross-correlation　coefficients　between　the　spectra　of　noisy　speech　and　noise　are　used　to　modify　the　spectral　gains　of　speech　and　noise.　Finally,　the　noisy　speech　is　passed　through　the　reconstructed　Wiener　filter　to　obtain　the　enhanced　speech.　The　objective　and　subjective　tests　show　that　the　performance　of　removing　annoying　background　noise　occurred　in　the　unvoiced　segments　or　silence　segments　is　much　better　than　the　conventional　codebook-based　method.