Abstract:
Mismatch in speech bandwidth between training and real operation greatly degrades the performance of automatic speech recognition (ASR) systems. Missing feature technique...Show MoreMetadata
Abstract:
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.
Published in: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date of Conference: 22-27 May 2011
Date Added to IEEE Xplore: 11 July 2011
ISBN Information: