A Missing Data Approach for Robust Automatic Speech Recognition in the Presence of Reverberation

We describe a technique for robust recognition of reverberated speech using the ‘missing data’ paradigm. Modulation filtering is used to identify time-frequency regions of the speech signal which are relatively uncontaminated by reverberation and contain strong speech energy; only these ‘reliable’ acoustic features are made directly available to the recogniser. The proposed system is evaluated on a connected digit recognition task using a range of reverberation conditions. Our approach improves recognition performance when the T60 reverberation time is longer than 0.7 sec., relative to a baseline system which uses acoustic features derived from perceptual linear prediction and the modulation filtered spectrogram.