The　identification　of　echolocation　clicks　signals　is　of　great　important　in　protection　and　research　in　marine　life.　Indo-Pacific　humpbacked　dolphin　is　first　class　national　protected　animals,　previous　research　has　proved　that　the　different　region　Indo-Pacific　humpbacked　dolphin　has　accent　of　their　own　species　groups.　An　artificial　neural　network　is　proposed　for　dolphin　species　identification　in　this　paper.　The　clicks　signals　were　detected　by　Teager-Kaiser　Energy　Operator　(TKEO),　then　cepstrum　operation　were　applied　to　the　clicks　signals　for　better　feature　representation　before　feed　in　the　neural　network.　Experiment　were　conducted　based　on　signals　of　Indo-Pacific　humpbacked　dolphins　from　both　Xiamen　and　Leizhou　Bay.　The　accuracy　of　species　identification　was　up　to　99%　and　optimal　choice　of　hyperparameter　of　neural　network　for　this　task　is　discussed.　©　2018　IEEE.