Abstract
An improved method for phoneme recognition in noise is presented using an auditory image model and cross-correlation in a binaural approach called the binaural auditory image model (BAIM). Current binaural methods are explained as background to BAIM processing. BAIM and a variation of the cocktail-party-processor incorporating the auditory image model are applied in phoneme recognition experiments. The results show BAIM performs as well or better than current methods for most signal-to-noise ratios.
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