Combining auditory perception and visual features for regional recognition of Chinese folk songs

Abstract

The regional recognition of Chinese folk songs is not only conducive to discovering music characteristics and regional styles of specific geographical folk songs, but also has important research value in the existing music information retrieval system. In this paper, an effective and novel approach for regional recognition of Chinese folk songs is proposed, which is based on the fusion of auditory perception and visual features using an ensemble SVM classifier. When the auditory perception features are extracted, the temporal relation among the frame features is fully considered. For the visual features, the color time-frequency maps are used to replace the gray-scale images to capture more texture information, and in order to better characterize the image texture, the texture patterns and the corresponding intensity information are both extracted. Experimental results show that the recognition method combined with auditory perception and visual features can effectively identify Chinese folk songs of different regions with an accuracy rate of 89.29%, which outperforms other state-of-the-art approaches.