Novel techniques for audio music classification and search
Kristopher West, Stephen Cox, Ben P. Milner, Josh D Reiss · ACM SIGMultimedia Records · 2009
This thesis presents a number of modified or novel techniques for the analysis of music audio for the purposes of classifying it according genre or implementing so called 'search-by-example' systems, which recommend music to users and generate playlists and personalised radio stations. Novel procedures for the parameterisation of music audio are introduced, including an audio event-based segmentation of the audio feature streams and methods of encoding rhythmic information in the audio signal. A large number of experiments are performed to estimate the performance of different classification algorithms when applied to the classification of various sets of music audio features. The experiments show differing trends regarding the best performing type of classification procedure to use for different feature sets and segmentations of feature streams.