With　the　rapid　development　of　the　Internet,　voice　recognition　has　become　one　of　the　core　technologies　on　information　era.　Bird　monitoring　through　sound　recognition　can　be　used　as　an　effective　indicator　of　wetland　environmental　quality.　In　this　paper,　we　use　Python　to　classify　birds　based　on　the　features　of　Mel　frequency　cepstrum　coefficient　via　K-Nearest　Neighbor,　support　vector　machine　and　multi-layer　perceptron.　Further,　we　carry　out　the　comparisons　of　these　algorithms　and　propose　a　novel　classifier　on　the　base　of　them.　The　experimental　results　show　that　the　new　classifier　absorbs　the　fast　prediction　speed　of　the　Multi-Layer　Perception,　the　high　accuracy　and　strong　noise　immunity　of　the　K-Nearest　Neighbor.　©　2022　ACM.