The Effect of Audio Degradation on Onset Detection Systems
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Date
2022-03-08
Authors
Ištvánek, Matěj
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Mark
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International Society for Science and Engineering, o.s.
Abstract
Although many articles in the field of Music Information Retrieval have been introduced to improve onset detection systems, only the bare minimum focus on the degradation of input audio to increase detection accuracy. This article evaluates the accuracy of five onset detectors, including stateof- the-art machine and non-machine learning-based systems, and compares the influence of various types of audio signal degradation on musical onset detection. We used three different degradations based on impulse responses, Teager–Kaiser energy operator, and two MP3 compression settings. The results suggest that if MP3 compression of any settings is applied, the accuracy of detection systems is very similar. Using the energy operator as degradation has not improved overall detection but may offer the potential of pre-processing the neural network input signal for easier identification of onsets in a training phase. Furthermore, radio broadcast degradation increases the number of all predicted onsets in general, both true and false positives, resulting in better recall but worse precision. This information could be used to modify the pre-processing phase of neural network-based detectors and to optimize the sensitivity trade-off.
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Elektrorevue. 2022, vol. 24, č. 1, s. 1-13. ISSN 1213-1539
http://elrevue.utko.feec.vutbr.cz/index.php/Elektrorevue/article/view/179/187
http://elrevue.utko.feec.vutbr.cz/index.php/Elektrorevue/article/view/179/187
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Peer-reviewed
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en
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(C) 2022 Elektrorevue