In　order　to　detect　whether　there　is　copy-move　forgery　in　an　audio　file,　a　new　algorithm　is　proposed　in　this　paper.　In　this　algorithm,　some　syllables　are　obtained　by　segmenting　audio　signal　with　voice　activity　detection　(VAD)　algorithm.　Discrete　cosine　transform　(DCT)　is　performed　to　process　these　syllables　to　generate　DCT　coefficients.　Then　these　coefficients　corresponding　to　every　syllable　are　converted　to　a　square　matrix.　After　that,　singular　value　decomposition　(SVD)　transform　is　performed　for　the　square　matrix　to　obtain　singular　eigenvector.　Here,　the　contribution　rate　is　calculated　to　reduce　the　dimension　of　the　singular　eigenvector.　So　the　amount　of　data　to　be　processed　can　be　reduced　greatly.　Finally,　the　distances　among　syllables　are　measured　by　comparing　the　distance　among　the　low-dimensional　singular　vectors　to　determine　whether　there　is　the　copy-move　relationship　between　corresponding　syllables.　Because　these　singular　values　have　a　great　stability,　the　distance　between　two　syllables　would　have　little　change　after　the　common　signal　processing.　The　low-dimension　singular　eigenvector　requires　less　computational　complexity,　so　the　algorithm　costs　less　running　time.　The　experiment　results　show　that　the　proposed　algorithm　is　robust　against　conventional　attacks　and　has　better　efficiency.