Suppression of acoustic noise in speech using two microphone adaptive noise cancellation

Acoustic noise with energy greater or equal to the speech is suppressed by filtering a separately recorded correlated noise signal and subtracting it from the speech waveform. This approach was investigated to determine the degree of noise suppression possible using an external correlated input. The second reference noise signal is adaptively filtered using the least mean squares, LMS and the lattice gradient algorithms. These two approaches are developed and compared in terms of degree of noise power reduction, algorithm convergence time, and degree of speech enhancement. Both methods were shown to reduce ambient noise power by at least 20dB with minimal speech distortion and thus to be potentially powerful as noise suppression preprocessors for voice communication in severe noise environments.