Cover Song Identification through Symbolic Representation and Classifier
D. Khasim Vali1, Nagappa U. Bhajantri2
1D. Khasim Vali*, Department of computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India.
2Nagappa U. Bhajantri, Department of computer Science and Engineering, Government College of Engineering, Chamarajanagara, India.
Manuscript received on February 02, 2020. | Revised Manuscript received on February 10, 2020. | Manuscript published on March 30, 2020. | PP: 735-740 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7183038620/2020©BEIESP | DOI: 10.35940/ijrte.F7183.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this work, we propose a work erected to cover song identification riding through a Symbolic Classifier. The classification of a cover song, which is a different variety of an earlier noted song for music retrieval, has received extra consideration. However, there is an urgency to protect the interest of melody music contributors. In view of this, several efforts have been heaping in literature. Systems for Classifying a cover song typically involved in Preprocessing, Extraction of Chroma features and Finally a Symbolic classifier for Identification.
Keywords: Beat Tracking, Chroma Features, Classifiers, Symbolic Representation.
Scope of the Article: Knowledge Representation and Retrievals.