For　efficient　coding　of　speech,　it　is　desirable　to　separate　the　slowly　and　rapidly　evolving　spectral　components　to　take　advantage　of　their　different　perceptual　qualities.　Existing　decomposition　methods　are　too　inflexible　to　model　transient　changes　in　the　speech　signals,　require　high　delay　or　produce　a　large　parameter　set　that　is　not　scalable　to　low　rates.　In　this　paper,　we　present　a　low　complexity　decomposition　method,　based　on　SVD,　applied　to　Waveform　Interpolation　(WI)　coding.　This　scheme　reduced　the　computational　complexity　of　common　SVD　method　in　WI　by　exploiting　the　properties　of　human　auditory　perception　to　lower　the　dimensions　of　decomposition　matrix.　This　method　requires　only　a　single　frame　of　speech　and　overcomes　the　substantial　delay　problems.　The　quantization　solution　involves　the　use　of　vector　quantization　on　separately　decomposed　the　singular　matrix　U　V　and　the　diagonal　matrix　of　singular　values　S.　The　quality　of　reconstruction　speech　can　be　varied　according　to　the　scalable　decomposition　and　the　bit　rate　available.　©2004　IEEE.