Li Deng, J. Wu, Jasha Droppo, and Alex Acero
Two feature extraction and compensation algorithms, feature-space minimum phone error (fMPE), which contributed to the recent significant progress in conversational speech recognition, and stereo-based piecewise linear compensation for environments (SPLICE), which has been used successfully in noise-robust speech recognition, are analyzed and compared. These two algorithms have been developed by very different motivations and been applied to very different speech-recognition tasks as well. While the mathematical construction of the two algorithms is ostensibly different, in this report, we establish a direct link between them. We show that both algorithms in the run-time operation accomplish feature extraction/compensation by adding a posterior-based weighted sum of “correction vectors,” or equivalently the column vectors in the fMPE projection matrix, to the original, uncompensated features. Although the published fMPE algorithm empirically motivates such a feature extraction operation as “a reasonable starting point for training,” our analysis proves that it is a natural consequence of the rigorous minimum mean square error (MMSE) optimization rule as developed in SPLICE. Further, we review and compare related speech-recognition results with the use of fMPE and SPLICE algorithms. The results demonstrate the effectiveness of discriminative training on the feature extraction parameters (i.e., projection matrix in fMPE and equivalently correction vectors in SPLICE). The analysis and comparison of the two algorithms provide useful insight into the strong success of fMPE and point to further algorithm improvement and extension.
|Published in||IEEE Signal Processing Letters|
|Publisher||Institute of Electrical and Electronics Engineers, Inc.|
© 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.