In　this　paper,　a　single-channel　speech　enhancement　method　based　on　generalized　weighted　beta-order　spectral　amplitude　estimator　is　proposed.　First,　we　derive　a　new　kind　of　generalized　weighted　beta-order　Bayesian　spectral　amplitude　estimator,　which　takes　full　advantage　of　both　the　traditional　perceptually　weighted　estimators　and　beta-order　spectral　amplitude　estimators　and　can　obtain　flexible　and　effective　gain　function.　Second,　according　to　the　masking　properties　of　human　auditory　system,　the　adaptive　estimation　methods　for　the　perceptually　weighted　order　p　is　proposed,　which　is　based　on　a　criterion　that　inaudible　noise　may　be　masked　rather　than　removed.　Thereby,　the　distortion　of　enhanced　speech　is　reduced.　Third,　based　on　the　compressive　nonlinearity　of　the　cochlea,　the　spectral　amplitude　order　beta　can　be　interpreted　as　the　compression　rate　of　the　spectral　amplitude,　and　then　the　adaptive　calculation　method　of　parameter　beta　is　proposed.　In　addition,　due　to　one　frame　delay,　the　a　priori　SNR　estimation　of　decision-directed　method　in　speech　activity　periods　is　inaccurate.　In　order　to　overcome　the　drawback,　we　present　a　new　a　priori　SNR　estimation　method　by　combining　predicted　estimation　with　decision-directed　rule.　The　subjective　and　objective　test　results　indicate　that　the　proposed　Bayesian　spectral　amplitude　estimator　combined　with　the　proposed　a　priori　SNR　estimation　method　can　achieve　a　more　significant　segmental　SNR　improvement,　a　lower　log-spectral　distortion　and　a　better　speech　quality　over　the　reference　methods.　(C)　2014　Elsevier　B.V.　All　rights　reserved.