Classification of Melodic Structures Using Fuzzified n-Gram Matching Scores

This paper reports classification of classical Indian melodic structures (Ragas) using a Fuzzy Multi Attribute Decision Model constructed using string matching scores. Sixteen clippings belonging to four different Ragas were matched with standard templates of the Ragas with an aim to detect the occurrences of subsets of the standard templates within a test string. Matching score obtained with subsets of varying lengths (n-grams) have been analyzed using Fuzzy Analytical Hierarchy Process (FAHP). Matching scores were first fuzzified by assigning them fuzzy memberships. Subsequently, 2, 3 and 4 gram scores were chosen as criteria/attributes against which four alternatives were evaluated. This paper proposes the use of fuzzy entropy for calculating the relative weights for each fuzzy set in the FAHP model. It was observed that classification success rate improved significantly when the n-gram scores were fuzzified and the proposed technique was applied.