Suffix tree indexing for music information retrieval

This thesis intended for fast and reliable data retrieval from music databases. It introduces new data reduction and indexing approaches for both polyphonic and monophonic music sequences.The study contributes to the literature from three aspects. These are data reduction, suffix tree indexing and tree alignment on external memory. In terms of data reduction, we present a new melody extraction approach for polyphonic music sequences. The new melody extraction approach considers the pitch histogram, and entropy of music sequences. Consequently, accompany channels of the MIDI music sequences are determined for data reduction. In terms of indexing, we present a new suffix tree construction approach for streaming music sequences. Current suffix tree construction algorithms have leaks about indexing music sequences. Hence, we adapted the physical structure of suffix trees for music notes. At last, we consider balance and alignment of suffix trees. In music, alphabet size of music is large. Therefore, we present clustering of music sequence. Therefore each sequence cluster can be indexed by a separate suffix tree to balance the tree.Both our melody extraction and suffix tree construction approaches are tested in detail and discussed. Our evaluation metrics are based on cognition, mathematical proofs and simulations. Experimental results showed that our approaches outperforms.