Interactive music systems: machine listening and composing
Interactive music systems: machine listening and composing
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
The computer music tutorial
A fast algorithm for computing longest common subsequences
Communications of the ACM
Stochastic Error-Correcting Syntax Analysis for Recognition of Noisy Patterns
IEEE Transactions on Computers
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Music is an important component of digital libraries. This paper discusses a digital music library from the information retrieval viewpoint and proposes a method for extracting theme phrases. These are then used to present a shorter version of retrieved music to users. The method consists of two steps, phrase extraction and syntactical classication of segmented fragments of melodies. Phrase extraction is carried out based on a few heuristic rules. We conducted an experiment on the accuracy of phrase extraction using 94 Japanese popular songs and obtained 0.766 recall and 0.786 precision. The syntactical classification is based on a probabilistic syntactical pattern analysis combining classification and syntactical analysis. The proposed method uses a decision tree and a finite state automaton and obtained 0.884 accuracy in theme phrase extraction.