Abstract
The howling varies depending on the room environment and it is difficult to predict the howling. In this research work, we develop spectro-temporal features for howling frequency detection. For the detection of howling frequency, several techniques have been developed such as least mean square method. The proposed approach is based on statistical properties of temporal power spectra, which requires less computational complexity than conventional methods. The proposed method is experimentally shown to be suitable for applications in sound systems.
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Lee, JW., Choi, S.H. (2012). Spectro-Temporal Features for Howling Frequency Detection. In: Kim, Th., Mohammed, S., Ramos, C., Abawajy, J., Kang, BH., Ślęzak, D. (eds) Computer Applications for Web, Human Computer Interaction, Signal and Image Processing, and Pattern Recognition. ICHCI WSE SIP 2012 2012 2012. Communications in Computer and Information Science, vol 342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35270-6_4
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DOI: https://doi.org/10.1007/978-3-642-35270-6_4
Publisher Name: Springer, Berlin, Heidelberg
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