A new look at discriminative training for hidden Markov models
Pattern Recognition Letters
On maximum mutual information speaker-adapted training
Computer Speech and Language
Discriminative training of HMMs for automatic speech recognition: A survey
Computer Speech and Language
BT*: an advanced algorithm for anytime classification
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Use of contexts in language model interpolation and adaptation
Computer Speech and Language
Maximum expected BLEU training of phrase and lexicon translation models
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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The well-known Baum-Eagon inequality (1967) provides an effective iterative scheme for finding a local maximum for homogeneous polynomials with positive coefficients over a domain of probability values. However, in many applications the goal is to maximize a general rational function. In view of this, the Baum-Eagon inequality is extended to rational functions. Some of the applications of this inequality to statistical estimation problems are briefly described