Improved noise minimum statistics estimation algorithm for using in a speech-passing noise-rejecting headset

Authors:
Saeed Seyedtabaee;Hamze Moazami Goodarzi
Affiliations:
Department of Electrical Engineering, Engineering Faculty, Shahed University, Tehran, Iran;Department of Electrical Engineering, Engineering Faculty, Shahed University, Tehran, Iran
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on robust processing of nonstationary signals
Year:
2010

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Abstract

This paper deals with configuration of an algorithm to be used in a speech-passing angle grinder noise-canceling headset. Angle grinder noise is annoying and interrupts ordinary oral communication. Meaning that, low SNR noisy condition is ahead. Since variation in angle grinder working condition changes noise statistics, the noise will be nonstationary with possible jumps in its power. Studies are conducted for picking an appropriate algorithm. A modified version of the well-known spectral subtraction shows superior performance against alternate methods. Noise estimation is calculated through a multi-band fast adapting scheme. The algorithm is adapted very quickly to the non-stationary noise environment while inflecting minimum musical noise and speech distortion on the processed signal. Objective and subjective measures illustrating the performance of the proposed method are introduced.