1. Scheme for Improved Residual Echo Cancellation in Packetized Audio Transmission Jivesh Govil Digital Signal Processing Laboratory Department of Electronics and Communication Netaji Subhas Institute of Technology University of Delhi, New Delhi, India Communication Systems, Networks and Digital Signal Processing, 19-21 July 2006 University of Patras, Patras, Greece Now a PhD Candidate at University of Michigan, Ann Arbor (USA)

2. How the road goes… ►Echo cancellation has put forth many challenging requirements ►Adaptive filter echo cancellation algorithm only in the active region ►Estimation of the constant delay and location of the active regions ►Integration with the Fast LMS/Newton algorithm ►Residual echo cancellation scheme based on the autoregressive (AR) analysis ►Residual echo is whitened by the inverse filter using the estimated AR coefficients Powerful echo cancellation for commercial mobile communication

3. The map of the road… E xplanatory Figure for the Proposed Scheme

4. Proposed scheme for Residual Echo Cancellation using Estimation of Delay and Fast LMS/Newton Algorithm The picture of the road…

5. The First Milestone… Improvement using Estimation of Delay - I Typical echo path impulse response ►Echo path impulse response consists of a constant time delay in which there is no echo signal and an active region with an echo signal No use of taps in flat region Faster Convergence Lower Computational Complexity ►Initial time delay-> “flat delay”

6. Improvement using Estimation of Delay - II Flat Delay Existence in  Satellite Communications  as high as 600ms  GSM- GWMSC/MSC  Because speech coding requires processing a frame of microphone signal to extract feature parameters  If echo cancellation algorithm is located in the wireless network rather than embedded in handset, the delay will be much longer  VoIP: Jitter Buffer Delays Flat delays exist in any frame-by-frame processing devices, from system to system, and from call to call

7. Improvement using Estimation of Delay - III Delay estimation module I Delay estimation module II  The scheme covers the active region via delaying x(n) by T1 samples, where T1 is the estimated flat delay and is the output of the delay estimation Module 2.  Module 1 produces a rough estimate of the flat delay (T 0 )  Module 2 produces the final refined estimate (T 1 )

8. Improvement using Estimation of Delay - IV Higher Performance Lower Cost Benefits ERLE (dB) Removed delay in echo path With delay in the echo path Samples ERLE curves for an echo path with and without delay

9. The Fast LMS/Newton algorithm † `  Possesses the attractive properties of regular hardware implementation  More stable adaptation than the FNTF The Second milestone… Fast LMS/Newton Algorithm for Adaptive Echo Cancellation † B. Farhang-Boroujeny, “Fast LMS/Newton Algorithm Based on Autoregressive Modeling and Their Applications to Acoustic Echo Cancellation," IEEE Trans. on Signal Processing, vol. 45, No. 8, pp. 1987- 2000,Aug 1997 TIME (Sec) ERLE (dB) Residual error versus time for Fast LMS and Normalized LMS (NLMS) Algorithm ERLE for NLMS and Fast LMS in case of time invariant echo response. Solid line: Fast LMS/Newton Algorithm;dashed line: Normalized LMS Fast LMS/Newton Algorithm Normalized LMS Algorithm

10. The Third Milestone… Improved Residual Echo Cancellation using Autoregressive Modeling - I  Use of Postprocessors  Distortion effects  Use of Voice Activity Detector (VAD)  Speech characteristics leading to misjudgments  Residual echo cancellation scheme  Removal by whitening process

11.  Speech characteristics of residual echo removed by a whitening process  Whitened residual echo signal is applied to noise reduction system  Therefore VAD perceives the residual echo as the ambient noise  In the whitening process, oPth order AR analysis for the residual echo is performed oInverse filtering is applied by using the estimated AR coefficients Improved Residual Echo Cancellation using Autoregressive Modeling - II  Output is applied to noise reduction system (G)  Final emerging signal is sent to the far-end-terminal

12. Improved Residual Echo Cancellation using Autoregressive Modeling - III  For a highly noisy environment, a test was performed to collect data in the moving car at 100 km/h  Performance of the AEC-only system was noticeably deteriorated by the ambient noise  This is compensated by using noise reduction as a postprocessor ╠By applying the residual echo cancellation method, the ERLE performance is improved further ╠The proposed system can be easily integrated ERLE (dB) TIME (Sec) ERLE curves for the moving car at 100 km/h (N=256). Solid line: the proposed system; dashed line: the conventional system (using post-processors); dashed- dotted line: the AEC–only system.

13. The Essence The end of the road… Conclusion ►Of great interest not only to traditional telephone system but also to Voice over IP, Voice over Cable, Voice over DSL, Satellite transmission systems and CDMA systems. ►Higher performance due to estimation of delay ►Can be enhanced for applications where there are multiple flat delays and active regions in the system ►Use of Fast LMS algorithm renders the system more tailored towards VLSI implementation ►Residual echo cancellation scheme can be used for hands- free telephony Very powerful approach for echo cancellation problems for variety of applications Estimation of Delay Fast LMS/Newton Algorithm AR Analysis & Inverse filtering