A new robust double-talk detector based on the Stockwell transform for acoustic echo cancellation |
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Affiliation: | 1. DSSE, Habib University, Karachi 75290, Pakistan;2. Department of Electrical Engineering and the Center for Communication Systems and Sensing, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia;3. Institut Universitaire de France (IUF), University of Orleans, PRISME Lab, Orleans 45072, France |
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Abstract: | Despite great developments in the field of acoustic echo cancellation (AEC), the presence of double-talk remains difficult problem. The main role of double-talk detection (DTD) is to control adaptation of the filter coefficients by halting their update in double-talk situations. In this paper, we propose a new method of DTD based on a time–frequency analysis that uses the Stockwell transform (ST).The ST is a time–frequency spectral localization method that combines the characteristics of the short-time Fourier transform and the wavelet transform. This method provides better time–frequency resolution, especially for non-stationary signals. In the experimental tests, the normalized least mean squares (NLMS) algorithm is used to update the filter coefficients along with speech signals taken from the TIMIT database. The obtained results show better performance compared to existing methods in terms of misalignment convergence and speech intelligibility enhancement. |
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Keywords: | Acoustic echo cancellation Double-talk detection Geigel Singular value decomposition Stockwell transform |
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