This　paper　presents　a　method　of　features　extraction　in　Speaker　Recognition.　This　method　divides　voice　signal　into　two　parts　based　on　the　MPEG　Psychological　Model　I,　and　processes　them　respectively.　And　then　we　analyze　the　extracted　MFCC　parameters,　and　compare　the　partition　of　frequency-band　between　Mel-spaced　filter　group　and　wavelet　packet　decomposition.　We　extract　the　coefficients　by　Wavelet　Package　Transform　(called　＇WPTC＇)　as　diagnostic　parameters　used　in　the　Speaker　Recognition.　The　results　of　experiments　indicated　that　it　perform　well　than　MFCC　while　using　the　WPTC　based　on　MPEG-1.　©　2008　IEEE.