An Acoustic Echo Canceller using Moving Window to Track Energy Variations of Double-Talk-Detector
Subject Areas : Signal ProcessingMouldi MAKDIR 1 * , Mourad BENZIANE 2 , Mohamed BOUAMAR 3
1 - Department of Electronics, Faculty of Technology, University of M’sila, M’sila, 28000, Algeria
2 - Laboratory of Analysis of Signals and Systems, M’sila, 28000, Algeria
3 - Department of Electronics, Faculty of Technology, University of M’sila, M’sila, 28000, Algeria
Keywords: AEC, DTD, NLMS, NCC, Moving Window,
Abstract :
As a fundamental device in acoustic echo cancellation (AEC) systems, the echo canceller based on adaptive filters relies on the adaptive approximation of the echo-path. However, the adaptive filter must face the risk of divergence during the double-talk periods when the near-end is present. To solve this problem, the double-talk-detector (DTD) is often used to detect the double-talk periods and prevent the echo canceller from being disturbed by the other end of the speaker’s signal. In this paper, we propose a DTD based on a new method that can detect quickly and track accurately double-talk periods. It is based on the sum of energies of the estimated echo and the microphone signals which is continuously compared to the error energy. A window that moves with time and tracks energy variations of the different input signals of the DTD represents a fundamental feature of the proposed method compared to several other methods based on correlation. The goal is to outperform conventional normalized cross-correlation (NCC) methods which are well-known in terms of small steady-state misalignment and stability of decision variable. In this work, the normalized least mean squares (NLMS) algorithm is used to update the filter coefficients along speech signals which are taken from the NOIZEUS database. Efficiency of the proposed method is particularly compared to the conventional Geigel algorithm and normalized cross-correlation method (NCC) that depends on the cross-correlation between the microphone signal and the error signal of AEC. Performance evaluation is confirmed by computer simulation.
[1] J. Benesty, T. Gänsler, D. R. Morgan, M. M. Sondhi, S. L. Gay, “Advances in network and acoustic echo cancellation. Digital Signal Processing,” Springer, Berlin, Heidelberg, 2001.
[2] M. M. Sondhi, “An adaptive echo canceler,” The Bell Syst, Technical journal, Vol. 46, No. 3, 1967, pp. 497–511.
[3] J. M. Gil-Cacho, “Adaptive filtering algorithms for Acoustic Echo Cancellation and Acoustic feedback control in speech communication applications,” PhD. Thesis, University of Belgium Ku Leuven, 2013.
[4] S. Haykin, “Adaptive filter Theory,” Prentice-Hall, Inc, Upper Saddle River, NJ, USA, 1996.
[5] J. Benesty, T. Gänsler, “Audio signal processing for next generation multimedia communication systems,” Kluwer Academic Publishers, 2004.
[6] F. Huang, J. Zhang, S. Zhang, “Combined-step size affine projection sign algorithm for robust adaptive filtering in impulsive interference environments,” IEEE Transactions on Circuits and Systems II: Express Briefs, Vol. 63, No. 5, 2015, pp. 493-497.
[7] Y. R. Chien, J. Li-You, “Convex combined adaptive filtering algorithm for acoustic echo cancellation in hostile environments,” IEEE Access, Vol. 6, 2018, pp. 16138-16148.
[8] D. Duttweiler, “A twelve-channel digital echo canceler,” IEEE Transactions on Communications, Vol. 26, No. 5, 1978, pp. 647-653.
[9] H. Ye, B. X. Wu, “A new double-talk detection algorithm based on the orthogonality theorem,” IEEE Transactions on Communications, Vol. 39, No. 39, 1991, pp. 1542-1545.
[10] J. Benesty, D. R. Morgan, J. H. Cho, “A new class of double-talk detectors based on cross-correlation,” IEEE Transactions on Speech and Audio Processing, Vol. 8, No. 2, 2000, pp. 168-172.
[11] M. A. Iqbal, J. W. Stokes, S. L. Grant, “Normalized double-talk detection based on microphone and AEC error cross- correlation,” IEEE International Conference on Multimedia and Expo, 2007, pp. 360-363.
[12] P. S. R. Diniz, “Adaptive Filtering Algorithms and Practical Implementation,” Springer, 2013.
[13] M. Hajiabadi, “Acoustic Noise Cancellation Using an Adaptive Algorithm Based on Correntropy Criterion and Zero Norm Regularization,” JIST Journal of Information Systems and Telecommunication, Vol. 3, No. 3, 2015, pp. 150-156.
[14] Hun, Choi.Hyeon-Deok, Bae, “Subband Affine Projection Algorithm for Acoustic Echo Cancellation System,” EURASIP Journal on Advances in Signal Processing, 2007, pp. 1-12.
[15] B. H. Yang, “An adaptive filtering algorithm for non-Gaussian signals in alpha-stable distribution,” Traitement du Signal, Vol. 37, No. 1, 2020, pp.69-75.
[16] S. Hannah, D. Samiappan , R. Kumar , A. Anand, A. Kar, “Variable tap-length non-parametric variable step-size NLMS adaptive filtering algorithm for acoustic echo cancellation,” Applied Acoustics, Vol. 159, 2020.
[17] M. Hamidia, A. Amrouche, “A new robust double-talk detector based on the Stockwell transform for acoustic echo cancellation,” Digital Signal Processing, Vol. 60, 2017, pp. 99-112. [18] V. Thien-An, H. Ding, M. Bouchard, “A survey of double-talk detection schemes for echo cancellation applications,” Canadian Acoustics, Vol. 32, No. 3, 2004, pp. 144-145. [19] M. Benziane, M. Bouamar, M. Makdir, “Doubletalk detection based on enhanced Geigel algorithm for acoustic echo cancellation,” In 2018 6th International Conference on Control Engineering & Information Technology (CEIT), 2018, pp. 1-5.
[20] T. Gänsler, J. Benesty, “A frequency-domain double-talk detector based on a normalized cross-correlation vector,” Signal Processing, Vol. 81, No 8, 2001, pp. 1783–1787.
[21] J. Benesty, T. Gänsler, “A multichannel acoustic echo canceler double-talk detector based on a normalized cross-correlation matrix*,” European Transactions on Telecommunications, Vol. 13, No 2, 2002, pp. 95–101.
[22] T. Gänsler, J. Benesty, “The fast normalized cross-correlation double-talk detector,” Signal Process, Vol. 86, No. 6, 2006, pp. 1124–1139.
[23] T. Gansler, M. Hansson, C.J.Ivarsson, G. Salomonsson, “A double-talk detector based on coherence,”IEEE Transactions on Communications, Vol. 44, No. 11, 1996, pp. 1421-1427.
[24] H. Bao, Y. Yang, J. Liu, X. Ba, Q. Yuan, “A robust algorithm of double talk detection based on voice activity detection,” Proc. Inter. conf. on Audio Language and Image Processing, 2010, pp. 12–15.
[25] S. Cecchi, L. Romoli, F. Piazza, “Multichannel Double-Talk Detector based on Fundamental Frequency Estimation,” IEEE Signal Processing Letters, Vol. 23, No. 1, 2016, pp. 94-97.
[26] Y. Zhenhai, F. Yang, J. Yang, “Optimum step-size control for a variable step-size stereo acoustic echo canceller in the frequency domain,” Speech Communication, Vol. 124, 2020, pp. 21–27.
[27] S. J. Park, C. G. Cho, C. Lee, D. H. Youn, S. H. Park, “Integrated echo and noise canceller for hands free applications,” IEEE Transactions on circuits and systems, Part II, Analog and Digital Signal Processing, Vol. 49, No. 3, 2002, pp. 188-195.
[28] Y. Hua, “Adaptive filter theory and applications,” PhD. Thesis, South-East university, China, 1989.
[29] Honig, M.L., Messerschmitt, D.G., “Adaptive Filters,” Kluwer, 1984.
[30] M. Benziane, M. Bouamar, M. Makdir, “Simple and Efficient Double-Talk-Detector for Acoustic Echo Cancellation,” Traitement du signal, Vol. 37, No. 4, 2020, pp. 585-592.
[31] ITU-T. “Digital Network Echo Cancellers,” Recommendation G.168, International Telecommunication Union; Geneva, 2007.
[32] Y. Hu, P. C. Loizou, “Subjective comparison and evaluation of speech enhancement algorithms,” Speech Communication , Vol. 49, No. 7, 2007, pp. 588-601.
[33] H. Wonchul, K. Taehwan, B. Keunsung, “Robust double-talk detection in the acoustic echo canceller using normalized error signal power,” Proc. ISSPA’07.UAE, 2007, pp. 1-4.
[34] J.H. Cho, D.R. Morgan, J. Benesty., “An objective technique for evaluating doubletalk detectors in acoustic echo cancelers,” IEEE Transactions on Speech and Audio Processing, Vol. 7, No. 6, 1999, pp. 718–724.
[35] ITU-T. “Digital Network Echo Cancellers,” Recommendation G.131, International Telecommunication Union; Geneva, 2003.