Content-based audio retrieval based on Gabor wavelet filtering

Rapid increase in the amount of audio data and especially music collections demand an efficient method to automatically retrieve audio objects based on its content. In this paper, based on the Gabor wavelet features, we will propose a method for content-based retrieval of perceptually similar music pieces in audio documents. It allows the user to select a reference passage within an audio file and retrieve perceptually similar passages such as repeating phrases within a music piece, similar music clips in a database or one song sung by different persons or in different languages. The proposed method will first divide an audio stream into clips, each of which contains one-second audio information. Then, the frame-based features of each clip are extracted based on the Gabor wavelet filters. Finally, a similarity measuring technique is provided to perform pattern matching on the resulting sequences of feature vectors. Experimental results show that the proposed method can achieve over 96% accuracy rate for audio retrieval.