Neural networks that employed unsupervised learning were used on the output of a binaural auditory model, know as the Cocktail-Party-Processor, to perform context-independent phoneme recognition. Experiments which compared the performance of the binaural model representation to that of a monaural version showed that the binaural model performed significantly better in terms of phoneme recognition accuracy under the conditions tested (low signal-to-noise ratios (SNR) and a small database of speakers). The binaural model representations' performance has approximately a 20 dB SNR advantage over the monaural representation.
Bibliographic reference. Bodden, Markus / Anderson, Timothy R. (1995): "A binaural selectivity model for speech recognition", In EUROSPEECH-1995, 127-130.