Compensation of partly reliable components for band-limited speech recognition with missing data techniques

Mismatch in speech bandwidth between training and real operation greatly degrades the performance of automatic speech recognition (ASR) systems. Missing feature technique (MFT) is effective in handling bandwidth mismatch. However, current MFT-based methods ignore the mismatch in the filter bank channels which cover the upper and lower limit cutoff frequencies. To solve this problem, we propose to partition the feature into reliable, unreliable and partly reliable parts, and then modify the probability density functions (PDFs) of the partly reliable part to match band-limited features. Experiments showed that such compensation further improved the performances of MFT-based methods under band-limited conditions.