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Implementation of blind source separation and a post-processing algorithm for noise suppression in cell-phone applications

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3 Author(s)
Devangi N. Parikh ; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, 30332, USA ; Muhammad Z. Ikram ; David V. Anderson

For cell-phone applications, single microphone noise suppression techniques have limited performance at very low SNR (close to 0 dB). In certain cases, they also suffer from the artifacts of nonlinear processing. In this paper, we will show that techniques based on two-microphone blind source separation (BSS) algorithm provide significant interference suppression for cell-phone applications, particularly at low operating SNR values. We also propose a post-BSS processing method based on frequency-domain spectral subtraction that further improves the BSS speech output in diffused noise case. We optimize the BSS algorithm so that it can be implemented on a low-power audio codec processor, which would be ideal for cell phone applications. Furthermore, based on extensive analysis under different noise and acoustic conditions, we suggest recommendations for optimal placement of microphones on a cell phone. We also study the trade-off between the unmixing filter length and the noise suppression performance. In all our experiments, we use real recordings made on a cell phone equipped with two microphones.

Published in:

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

14-19 March 2010