Harmonic models for polyphonic music retrieval
Proceedings of the eleventh international conference on Information and knowledge management
Problems of music information retrieval in the real world
Information Processing and Management: an International Journal
A New Method for Tracking Modulations in Tonal Music in Audio Data Format
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Harmonic modeling for polyphonic music retrieval
Harmonic modeling for polyphonic music retrieval
A new metric for probability distributions
IEEE Transactions on Information Theory
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A 24-dimensional model for the ‘harmonic content' of pieces of music has proved to be remarkably robust in the retrieval of polyphonic queries from a database of polyphonic music in the presence of quite significant noise and errors in either query or database document. We have further found that higher-order (1st- to 3rd-order) models tend to work better for music retrieval than 0th-order ones owing to the richer context they capture. However, there is a serious performance cost due to the large size of such models and the present paper reports on some attempts to reduce dimensionality while retaining the general robustness of the method. We find that some simple reduced-dimensionality models, if their parameter settings are carefully chosen, do indeed perform almost as well as the full 24-dimensional versions. Furthermore, in terms of recall in the top 1000 documents retrieved, we find that a 6-dimensional 2nd-order model gives even better performance than the full model. This represents a potential 64-times reduction in model size and search-time, making it a suitable candidate for filtering a large database as the first stage of a two-stage retrieval system.