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
Subject:
Posters: Production and Broadcast
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.