Speech Noise Reduction System Based on Adaptive Filter with Variable Step Size Using Cross-Correlation

In order to reduce background noise in noisy speech, we have investigated a noise reduction method based on a noise reconstruction system (NRS) with an adaptive line enhancer (ALE). The NRS uses a noise reconstruction filter (NRF) estimating the background noise. In case a fixed step size for updating tap coefficients of the NRF is used, it is difficult to estimate the background noise accurately while maintaining the high quality of enhanced speech. In order to improve the estimation accuracy of noise, a variable step size is introduced to the NRF. In a speech section, the variable step size decreases so as to become no sensitivity for speech, on the other hand, increases to track the background noise in a non-speech section. From simulation results, we have verified that the proposed system can reduce the actual noise while maintaining the high quality of enhanced speech.