In order to further improve the performance of methods for audio events clustering

this paper proposes a method for audio events clustering based on the theory of agglomerative information bottleneck.First

the principles and derivations of information bottleneck are briefly introduced.Then

the proposed method is described in detail

including the definitions of source variables

relevance variables and destination variables

the steps of the proposed method and the analyses of main computational loads of all methods.The proposed method and two kinds of previous methods (including the method based on spectral clustering

and the method based on both Bayesian information criterion and agglomerative hierarchical clustering) are evaluated on the experimental data extracted from two different corpora of audio events.The experimental results show that the proposed method obtains higher K values (geometric mean of average clustering purity and average audio purity) and runs faster than the previous methods under several experimental conditions.