A probabilistic union model for sub-band based robust speech recognition

A new statistical model is proposed for combining sub-band observations for robust speech recognition. This model characterizes the randomly corrupted sub-bands based on the union of random events. The new model has been incorporated into a hidden Markov model (HMM) and tested for recognizing a speaker-independent E-set, corrupted by various types of frequency-selective noise with unknown, time-varying statistics. The results show that the new model offers robustness to partial frequency corruption, requiring little or no knowledge about the noise characteristics