A series of psychoacoustic experiments is described which attempts to assess the suitability of the Multi-Microphone Sub-band Adaptive Signal (MMSBA) processing scheme [1] for improving the intelligibility of speech in noise. The process uses the Least Mean Squares (LMS) algorithm [2] in sub-bands to process speech signals from various acoustic environments and signal to noise ratios (SNR). The method aims to take advantage of the multiple inputs to perform noise cancellation. The wide-band signal is split into sub-bands, which are subsequently processed according to their signal characteristics. The results of a series of intelligibility tests are presented from experiments in which acoustic speech and noise data, generated in both simulated and real room conditions was presented to subject volunteers at various SNRs.