DocumentCode
763766
Title
Corrections to "Segmental minimum Bayes-risk decoding for automatic speech recognition"
Author
Goel, Vaibhava ; Kumar, Shankar ; Byrne, William
Author_Institution
IBM T. J. Watson Res. Center, Yorktown Heights, NY, USA
Volume
14
Issue
1
fYear
2006
Firstpage
356
Lastpage
357
Abstract
The purpose of this paper is to correct and expand upon the experimental results presented in our recently published paper [1]. In [1, Sec. III-B], we present a risk-based lattice cutting (RLC) procedure to segment ASR word lattices into sequences of smaller sublattices. The purpose of this procedure is to restructure the original lattice to improve the efficiency of minimum Bayes-risk (MBR) and other lattice rescoring procedures. Given that the segmented lattices are to be rescored, it is crucial that no paths from the original lattice be lost in the segmentation process. In the experiments reported in our original publication, some of the original paths were inadvertently discarded from the segmented lattices. This affected the performance of the MBR results presented. In this paper, we briefly review the segmentation algorithm and explain the flaw in our previous experiments. We find consistent minor improvements in word error rate (WER) under the corrected procedure. More importantly, we report experiments confirming that the lattice segmentation procedure does indeed preserve all the paths in the original lattice.
Keywords
Bayes methods; decoding; speech coding; speech recognition; automatic speech recognition; lattice rescoring procedures; lattice segmentation procedure; risk-based lattice cutting procedure; segmental minimum Bayes-risk decoding; word error rate; word lattices; Automatic speech recognition; Decoding; Error analysis; Lattices; Natural languages; Programmable control; Speech processing;
fLanguage
English
Journal_Title
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher
ieee
ISSN
1558-7916
Type
jour
DOI
10.1109/TSA.2005.854087
Filename
1561291
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