Use of Spectral Peaks in Autocorrelation and Group Delay Domains for Robust Speech Recognition

This paper presents a new front-end for robust speech recognition. Two scenarios are used for the features extracted in autocorrelation and group delay domains. These new front-end scenarios focuses on the spectral peaks of speech in two mentioned domains. Therefore we address the issue of using spectral peak location information in a feature vector for robust speech recognition. A task of speaker-independent isolated-word recognition was used to demonstrate the efficiency of these robust front-end diagrams. The cases of white noise and different colored noises such as babble, factory and car noises were tested. Experimental results show significant improvements in comparison to the results obtained using traditional front-end diagrams