Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5613
Title: Classification of audios containing speech and music
Other Titles: Konuşma ve müzi?k i?çeren sesleri?n ayriştirilmasi
Authors: Uzun, Erkam
Sencar, Hüsrev Taha
Issue Date: 2012
Source: 2012 20th Signal Processing and Communications Applications Conference, SIU 2012, 18 April 2012 through 20 April 2012, Fethiye, Mugla, 90786
Abstract: We propose an automated technique that uses perceptual and non-perceptual audio quality measures for discrimination of speech and music signals with high accuracy. Deployed audio quality measures used for characterization of audio are obtained via de-noising of the original audio. The underlying idea of the approach is that de-noising operation affects speech and music signals in a different and consistent manner and these differences can be captured by the audio quality metrics. Obtained quality measures are then used in conjunction with a machine learning classifier to statistically model speech and music signals. To determine the accuracy of the proposed method, tests have been performed on different datasets with and without audio compression. © 2012 IEEE.
URI: https://doi.org/10.1109/SIU.2012.6204616
https://hdl.handle.net/20.500.11851/5613
ISBN: 9781467300568
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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