This paper is published in Volume-3, Issue-6, 2017
Area
Signal Processing
Author
Sushen R. Gulhane, Dr. Suresh D. Shirbahadurkar, Sanjay Badhe
Org/Univ
D. Y. Patil College of Engineering, Pune, Maharashtra, India
Pub. Date
05 December, 2017
Paper ID
V3I6-1335
Publisher
IJARIIT
Edition
Volume-3, Issue-6, 2017
Keywords
Musical Instrument Recognition, Mel Frequency Cepstral Coefficient (MFCC), Fractional Fourier Transform (FRFT), Machine Learning Technique (KNN)

Citationsacebook

IEEE
Sushen R. Gulhane, Dr. Suresh D. Shirbahadurkar, Sanjay Badhe. KNN- A Machine Learning Approach to Recognize a Musical Instrument, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Sushen R. Gulhane, Dr. Suresh D. Shirbahadurkar, Sanjay Badhe (2017). KNN- A Machine Learning Approach to Recognize a Musical Instrument. International Journal of Advance Research, Ideas and Innovations in Technology, 3(6) www.IJARIIT.com.

MLA
Sushen R. Gulhane, Dr. Suresh D. Shirbahadurkar, Sanjay Badhe. "KNN- A Machine Learning Approach to Recognize a Musical Instrument." International Journal of Advance Research, Ideas and Innovations in Technology 3.6 (2017). www.IJARIIT.com.

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Abstract

In this paper, the methodology used to recognize the musical instrument is summarized. To recognize musical instruments, there are two ways. They are training phase & testing phase. The details regarding the same is mentioned. Music Information Retrieval toolbox is used to extract features of the input signals. There are no. of ways classifiers available out of which we have used KNN- a machine learning approach.

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