A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Discriminative Training for direct minimization of deletion, insertion and substitution errors
2011
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
In this paper, we follow the minimum error principle for acoustic modeling and formulate error objectives in insertion, deletion, and substitution separately for minimization during training. This new training paradigm generalized from the MVE criterion can explain the direct relationship between recognition errors and detection errors by re-interpreting deletion, insertion, and substitution errors as miss, false alarm, and miss/false-alarm errors happening together. Under the MVE criterion, by
doi:10.1109/icassp.2011.5947561
dblp:conf/icassp/ShinJJ11
fatcat:le3h6tzs5rhhfoqc5du73xx5mu