SASTech - Technical Journal of RUAS
  • Year: 2012
  • Volume: 11
  • Issue: 1

Design and Development of Noise Cancellation System for Android Mobile Phones

  • Author:
  • N. Ravikanth1, Sanket Dessai2
  • Total Page Count: 8
  • Page Number: 33 to 40

1M. Sc. [Engg.] Student, Department of Computer Engineering, M. S. Ramaiah School of Advanced Studies, Bangalore-560 058

2Assistant Professor, Department of Computer Engineering, M. S. Ramaiah School of Advanced Studies, Bangalore-560 058

Online published on 18 February, 2020.

Abstract

Background noise has always been undesirable in end user communication devices while conversing over a mobile phone if the speaker is on a busy road or noisy environment. Noise cancellation mechanism can be implemented in these mobiles devices to suppress the background noise and pass only speech signal to the other end. Android is fast growing mobiles phone and expanding to all segments of the market; thus a noise cancellation mechanism can benefit a wide range of user.

This paper describes the design and development of Noise Cancellation System (NCS) to cancel the background noise from the speech signal of speaker in android mobile phones. NCS system has been implemented using an adaptive filter, which changes its filter characteristic according to the change in behavior of the input signal to minimize the noise in signal. Least Mean Square (LMS) algorithm has been used for adapting the filter weights. The adaptive filter has two inputs one as desired signal corrupted by noise and another only background noise. Two separate microphones are used to capture these signals respectively; the regular microphone into which the speaker speaks captures signal with noise. The other microphone is directed away from the speaker and thus captures background noise. The system has been modelled and its performance tuned in MATLAB. The tuned adaptive filter is implemented in C on a GNU/Linux environment which is then ported to android SDK and tested for its functionality in android emulator. The tested NCS application has been installed on friendlyARM mini2440 board with android OS.

The performance of the adaptive filter has been compared with different filter taps and stepsize for speech signal. A filter length 128 and stepsize 0.9 for the adaptive filter in NCS provided the best performance. With these tuned parameters, the NCS application has been able to perform acceptable adaptive noise cancellation. The quality of the required signal can be further improved by enhancing the adaptive filter algorithm.

Keywords

Noise Cancellation, android, Adaptive Filter, LMS Algorithm, Friendly ARM