The invention discloses a complex audio segmentation clustering method based on a bottleneck feature. The method comprises the steps that a deep neural network with a bottleneck layer is constructed; a complex audio stream is read, and endpoint detection is carried out on the complex audio stream; the audio feature of a non-silent segment is extracted and input into the deep neural network; the bottleneck feature is extracted from the bottleneck layer of the deep neural network; the bottleneck feature is used as input, and an audio segmentation method based on the Bayesian information criterion is used, so that each audio segment contains only one kind of audio type and adjacent audio segments have different audio types; a spectral clustering algorithm is used to cluster segmented audio segments to acquire the number of audio types of complex audios; and the audio segments of the same audio type are merged together. According to the invention, the used bottleneck feature is a deep transform feature, can more effectively describe the feature difference of the complex audio type than a traditional audio feature, and acquires an excellent effect in complex audio segmentation clustering.