Comparison of Autoregressive Model Based Perceptible Click Detection Algorithms

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00358041" target="_blank" >RIV/68407700:21230/22:00358041 - isvavai.cz</a>
Result on the web
<a href="http://www.cvut.cz/poster" target="_blank" >http://www.cvut.cz/poster</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Comparison of Autoregressive Model Based Perceptible Click Detection Algorithms
Original language description
In this paper, Autoregressive (AR) model based click detection algorithms are compared in terms of their ability to detect only the perceptible impulsive noise (clicks) contained in the audio signals taken from damaged vinyl records. All the algorithms are using the same principle of detection but they are all improved differently in the mentioned literature. The test audio signals are previously classified to be containing or not containing clicks. Comparison criterion is based on a previously introduced custom function, defined through the correct and the false detection ratios. Run time comparisons of the algorithms are also made. Results showed that a Simple AR model algorithm performed the best, both in detection and in run time, amongst the compared AR algorithms.
Czech name
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Czech description
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Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the International Student Scientific Conference Poster – 26/2022
ISBN
978-80-01-06992-9
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
1-4
Publisher name
Fakulta elektrotechnická
Place of publication
Praha
Event location
Praha
Event date
May 12, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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