Speech　enhancement　is　an　important　issue　in　the　field　of　speech　signal　processing.　With　the　development　of　deep　learning,　speech　enhancement　technology　combined　with　neural　network　has　provided　a　more　diverse　solution　for　this　field.　In　this　paper,　we　present　a　new　approach　to　enhance　the　noisy　speech,　which　is　recorded　by　a　single　channel.　We　propose　a　phase　correction　method,　which　is　based　on　the　joint　optimization　of　clean　speech　and　noise　by　deep　neural　network　(DNN).　In　this　method,　the　ideal　ratio　masking　(IRM)　is　employed　to　estimate　the　clean　speech　and　noise,　and　the　phase　correction　is　combined　to　get　the　final　clean　speech.　Experiments　are　conducted　by　using　TIMIT　corpus　combined　with　four　types　of　noises　at　three　different　signal　to　noise　ratio　(SNR)　levels.　The　results　show　that　the　proposed　method　has　a　significant　improvement　over　the　referenced　DNN-based　enhancement　method　for　both　objective　evaluation　criterion　and　subjective　evaluation　criterion.　©　2018　APSIPA　organization.