Robust speech recognition based on neighborhood space

In this paper, we present an approach to robust speech recognition based on neighborhood space. To achieve performance robustness under mismatch between training and testing conditions, we propose to use neighborhood space of each underlying model to produce Bayesian predictive density as observation probability density. Experimental results show that the proposed method improves the performance robustness.