Title :
Binaural phoneme recognition using the auditory image model and cross-correlation
Author :
K.I. Francis;T.R. Anderson
Author_Institution :
Cedarville Coll., OH, USA
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.
Keywords :
"Image recognition","Signal to noise ratio","Feature extraction","Equations","Speech","Filters","Educational institutions","Laboratories","Neural networks","Ear"
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.596167