Adaptive noise cancelling in speech using the short-time transform

Acoustic noise in speech can be suppressed by filtering a separately recorded correlated noise signal and subtracting it from the speech waveform. In the time domain this adaptive noise cancelling approach requires a computational rate which is linear with filter length. This paper describes how to implement the noise cancelling procedure in the frequency domain using the short-time Fourier transform. Using the efficiency of the FFT results in a computation rate which is proportional to the log of the filter length. For acoustic noise suppression where the filter length can be on the order of one thousand points, this approach offers a viable alternative for real time implementation, The performance of this method is compared with the time domain methods on noisy speech having a noise power equal to the signal power and is shown to be equally effective as a noise cancelling preprocessor.