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SUB BAND ADAPTIVE NOISE CANCELLATION WITH MULTIRATE TECHNIQUE

In this paper a multirate solution in the form of sub band processing is presented. A mulltirate filter bank is used to divide the input noisy speech and the environmental noise into a number of channels and uses the Normalized Least Mean Square (NLMS) algorithm to control an adaptive finite Impulse Response (FIR) filter to reduce the noise in the input signal. A noise canceling model was developed, tested and compared to its equivalent full band model. This system was called the Over Sampled Sub band Noise Canceller (OSSNC) .The proposed structure gave about 10 dB noise reductions better than the full band model when tested with real life speech and acoustic background noise. The filter bank of this canceller was then modified by increasing the bandwidth of the analysis filter as compared to the synthesis filters in a predefined manner. The modified system was then called the Modified Over Sampled Noise Canceller (MOSSNC). This modification gave good improvements in convergence characteristics. The new system outperformed the OSSNC in initial and steady state convergence, and gave about 15 dB noise reductions better than the full band obtained when the canceller was subjected to actual speech and noise. In addition to the increase in speed adaptive filter convergence; this solution reduces the computational complexity to a certain extent.