The　Kalman　filtering　algorithm　for　speech　enhancement　is　easily　implemented　and　is　efficient　under　white　noise　environments.　This　paper　proposes　an　effective　Kalman　filtering　algorithm　for　enhancing　speech　corrupted　by　colored　noise,　based　on　a　whitened　matrix.　Compared　with　the　conventional　Kalman　filtering　algorithms　to　handle　colored　noise,　the　proposed　Kalman　filtering　algorithm　has　low　computational　complexity　and　overcomes　the　difficulty　of　estimating　the　covariance　matrix　of　colored　noise.　Simulation　results　confirm　that　the　proposed　Kalman　filtering　algorithm　has　better　performance　than　several　conventional　algorithms　in　decreasing　colored　noise　and　speech　distortion.