Indian Music Classification using Neural network based Dragon fly algorithm
Keywords:
Classification, ICM, NN, Raaga , SwarasAbstract
Generally, Indian Classical Music (ICM) is categorized into 2 Hindustani and Carnatic. Although, aforesaid music formats possess the same base, the presentation manner is different in numerous ways. The ICM basic modules are taala and raga. Fundamentally, Taala indicates rhythmic beats else patterns. From the flow of swaras, the raga is ascertained that is indicated as extensive terms. On the basis of few important factors, the raga is indicated namely aarohana-avarohna and swaras and distinctive phrases. In practice, the basic frequency is Swara that is exact via time period. In addition, there are numerous other issues with the automatic raga identification technique. Hence, raga is identified in this research without using precise note series information and vital to use an effectual classification technique. This research develops an effectual raga recognition model via the Carnatic genre music that is efficiently identified for the data mining models, which is also included. Here, the Neural Network (NN) model is proposed which is an adaptive classifier in that the feature set is exploited to learning, and the data mining models are used for the classification techniques. Moreover, a meta-heuristic approach is used for the adaptive classifier to obtain the extracted feature set knowledge. As the learning technique plays an important role in describing the accuracy of the raga identification model, it prefers to adopt the Dragonfly algorithm.
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