With　the　appearance　of　a　large　amount　of　audio　data,　people　have　a　higher　demand　for　audio　retrieval,　which　can　quickly　and　accurately　find　the　required　information.　Audio　fingerprint　retrieval　is　a　popular　choice　because　of　its　excellent　performance.　However,　there　is　a　problem　about　the　large　amount　of　audio　fingerprint　data　in　the　existing　audio　fingerprint　retrieval　method　which　takes　up　more　storage　space　and　affects　the　retrieval　speed.　Aiming　at　the　problem,　this　paper　presents　a　novel　audio　fingerprinting　method　based　on　locally　linear　embedding　(LLE)　that　has　smaller　fingerprints　and　the　retrieval　is　more　efficient.　The　proposed　audio　fingerprint　extraction　divides　the　bands　around　each　peak　in　the　frequency　domain　into　four　groups　of　sub-regions　and　the　energy　of　every　sub-region　is　computed.　Then　the　LLE　is　performed　for　each　group,　respectively,　and　the　audio　fingerprint　is　encoded　by　comparing　adjacent　energies.　To　solve　the　distortion　of　linear　speed　changes,　a　matching　strategy　based　on　dynamic　time　warping　(DTW)　is　adopted　in　the　retrieval　part　which　can　compare　two　audio　segments　with　different　lengths.　To　evaluate　the　retrieval　performance　of　the　proposed　method,　the　experiments　are　carried　out　under　different　conditions　of　single　and　multiple　groups＇　dimensionality　reduction.　Both　of　them　can　achieve　a　high　recall　and　precision　rate　and　has　a　better　retrieval　efficiency　with　less　data　compared　with　some　state-of-the-art　methods.