Retrieval of musical information from musical databases is a major challenging issue in a digital world. Therefore, it is necessary to develop an efficient tool for retrieving the musical information. Musical instrument classification plays a major role for retrieving the information from musical database. In order to retrieve the musical instrument efficiently, an enhanced musical instrument classification algorithm using deep Convolutional Neural Network is proposed in this paper. The proposed algorithm consists of convolutional layers interleaved with two pooling functions followed by two fully interconnected layers. There are sixteen instruments from different instrument families are taken for evaluating the performance of proposed algorithm. The experimental result shows that the proposed algorithm recognizes the instruments significantly and achieves the greater accuracy than existing algorithm.
CITATION STYLE
Prabavathy*, S., Rathikarani, V., & Dhanalakshmi, P. (2019). An Enhanced Musical Instrument Classification using Deep Convolutional Neural Network. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 8772–8774. https://doi.org/10.35940/ijrte.d9271.118419
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