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Audio feature extraction: Foreground and Background audio separation using KNN algorithm

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Pankaj Ramakant Kunekar, Koushal Sunil Sadavarte *, Prajwal Rajshekhar Khambad, Rohan Baban Lokhande and Manasi Babusha Kharat

Vishwakarma Institute of Technology, Pune, 411037, Maharashtra, India.

Review Article
 
International Journal of Science and Research Archive, 2023, 09(01), 269–276.
Article DOI: 10.30574/ijsra.2023.9.1.0392
DOI url: https://doi.org/10.30574/ijsra.2023.9.1.0392

Received on 09 April 2023; revised on 25 May 2023; accepted on 27 May 2023

Data Science is a fairly novel field, and it predominantly deals with analysis and assortment of data. Machine Learning is a field that goes hand in hand in this regard. Various Algorithms, which are trained on a dataset predict results based on their training, and thus the accuracy of a model is determined by the testing dataset. Foreground feature extraction is another interesting application. Using data visualization and processing, we can plot the graphs for the audio frequency and intensity. This proves useful in feature extraction using MFCC (Mel-frequency cepstral coefficients).

Data Science; Feature Extraction; Librosa; Machine Learning; Python

https://ijsra.co.in/sites/default/files/fulltext_pdf/IJSRA-2023-0392.pdf

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Pankaj Ramakant Kunekar, Koushal Sunil Sadavarte, Prajwal Rajshekhar Khambad, Rohan Baban Lokhande and Manasi Babusha Kharat. Audio feature extraction: Foreground and Background audio separation using KNN algorithm. International Journal of Science and Research Archive, 2023, 09(01), 269–276. Article DOI: https://doi.org/10.30574/ijsra.2023.9.1.0392

Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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