Feedback Cancellation in Public Address systems using notch filters Shailesh Kulkarni Vaibhav Mathur Digital Signal Processing-Advanced Topics

2 Presentation Outline Feedback in audio systems Design of feedback controller – Feedback detection method – Feedback cancellation Implementation and Results – Design of Notch Filter – Graphs and simulation Concluding Remarks

3 Feedback in audio systems

4 Acoustic coupling between microphone and loudspeaker Amplified sound at speaker output is propogated back to the microphone and re- amplified Causes oscillation of audible frequencies and high pitch howling sometimes Can cause physical damage to the audio equipment

5 Feedback Controller Feedback Detection notch filter Filterbank Audio Feedback frequencies IN OUT

6 Feedback Controller Feedback Detection Works on 1024 point buffer at a time Analyze frequencies with large magnitude Compare them with the harmonics to distinguish between signal and the feedback Candidate frequencies is passed to filter for removal Feedback Cancellation Design of notch filter Changes with every buffer

7 Feedback Detection block 1024 point BUFFER 1024 point FFT normalize FFT Compare f2max to harmonics Find 3 largest Mag. freq. F2max = feedback frequency Candidate in 3 out of 5 buffers? Compare fmax to harmonics Fmax = feedback frequency Candidate in 3 out of 5 buffers? Compare f3max to harmonics F3max = feedback frequency Candidate in 3 out of 5 buffers? Audio IN

8 F FB = NEW ? Set NEW notch filter Depth = 3 dB Increase depth of existing notch filter Depth = depth + 3 dB NO YES Width = 1/10 octave Feedb ack freq Design of Notch Filter

9 FB detection using Energy Threshold Alternative way to detect feedback Deals with relation between energy of the peak and the whole spectrum Value of Energy threshold determines the sensitivity of the detection

10 Notch Filter We use a parametric IIR filter r z = zero radius r p =pole radius(r)

11 Notch Filter Effect of r p – It affects the bandwidth and the depth of the Notch – As r p increases ( < r z ) the notch bandwidth becomes narrower – Also the notch depth decreases [1] We fixed r z to 1 so as to get large notch depth

12 Notch Filter - Simulation

13 Simulations

14 Simulations

15 Performance Metrics RMS as a measure – With feedback = – After filtering = – Improvement factor = 13 Audio

16 Concluding Remarks Requirement of better algorithm to detect feedback in the signal for performance improvement As number of samples per frame increases, we get better resolution in frequency But we trade delay and complexity

17 References [1] A. F. Rocha and A. J. S. Ferreira, "An accurate method of detection and cancellation of multiple acoustic feedbacks," Preprints 118th AES Conv., Barcelona, Spain, May 2005, Preprint no [2] T. van Waterschoot and M. Moonen, "A pole-zero placement technique for designing second-order IIR parametric equalizer filters," IEEE Trans. Audio, Speech, Lang. Process., vol. 15, no. 8, Nov. 2007, pp [3] P. A. Regalia and S. K. Mitra, "Tunable digital frequency response equalization filters," IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-35, no. 1, Jan. 1987, pp [4] U.S. Patent Number ;

18 Thank you Questions ?