In this article, an evaluation of a recently published hum detection algorithm for audio signals is presented. To determine the performance of the method, large amounts of artificially generated and real-world audio data, containing a variety of music and speech recordings, are processed by the algorithm. By comparing the detection results with manually determined ground truth data, several error measures are computed: hit and false alarm rates, frequency deviation of the hum frequency estimation, offset of detected start and stop times and the accuracy of the SNR estimation.

Authors: Brandt, Matthias; Schmidt, Thorsten; Bitzer, Joerg
Affiliations: Cube-Tec International, Bremen, Germany; Jade University of Applied Sciences, Oldenburg, Germany(See document for exact affiliation information.)
AES Convention: 130 (May 2011) Paper Number: 8395
Publication Date: May 13, 2011 Import into BibTeX
Subject: Posters: Production and Broadcast
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=15862

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