Soft set theory for automatic classification of traditional pakistani musical instruments sounds

Musical instrument classification has a great importance in data mining and multimedia. The number of studies investigating classification of musical instruments using sophisticated modeling such as neural networks, support vector machines, decision tress and rough set. However, the viability of soft set theory for musical instruments classification has not been widely experimented. Thus, this paper introduces a classification system which uses notation of soft set theory incorporating non-western musical instruments i.e. Traditional Pakistani Musical Instruments. One of the factors that may contribute to this phenomenon which are audio length, frame size and starting point of files have been investigated that might affect the performance of the classification algorithm. The modeling process comprises of three steps which are data-preprocessing, dataset partitioning and classification. Experimental results show that 94.26% was obtained from the generated datasets. Soft set theory provides fruitful investigation for musical instruments classification. These results have further expanded the scope of soft set theory for decision making applications.