This paper evaluates the ability of several algorithms to detect impulse distortions (clicks) in audio signals. The systems are evaluated against data from a listening test conducted using real audio signals provided by a vinyl manufacturer. Some of the signals contained clicks due to damage during the manufacturing process. An evaluation of click detection algorithms against listening test results focuses on the ability of the click-detection algorithms to detect perceptible clicks. The results presented in this paper show that an algorithm that employs a hearing model detected audible clicks with a lower false detection rate than the other algorithms in the test and that the wavelet transform–based algorithm with a dynamic threshold outperformed the other algorithms.
http://www.aes.org/e-lib/browse.cfm?elib=21123
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.
Learn more about the AES E-Library
Start a discussion about this paper!
