Abstract: Traditional example based audio retrieval algorithms use forward index, with which, retrieval processing need to traverse the whole database, resulting in intolerable response time. This paper proposes an inverted-index based audio retrieval method. Through constructing super-vector comprising several audio features, audio stream is first segmented into short segments with small feature fluctuation; Based on a pre-trained audio word dictionary, short audio segment sequence is then transformed into audio word sequence, from which inverted index is constructed; During the retrieval phase, the query audio sample is transformed into audio words and retrieval is carried out, candidate segments are ranked according to the similarity with the query. Match term ranking, same type ratio, overlap ratio and retrieval time are used to evaluate the performance of the proposed algorithm. The experiment gives 92.58% retrieval precision within average response time of 1.101 s.