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» Improving Language Models by Clustering Training Sentences
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INTERSPEECH
2010
13 years 2 months ago
Investigation of full-sequence training of deep belief networks for speech recognition
Recently, Deep Belief Networks (DBNs) have been proposed for phone recognition and were found to achieve highly competitive performance. In the original DBNs, only framelevel info...
Abdel-rahman Mohamed, Dong Yu, L. Deng
COLING
2000
13 years 9 months ago
Improving SMT quality with morpho-syntactic analysis
In the framework of statistical machine translation (SMT), correspondences between the words in the source and the target language are learned from bilingual corpora on the basis ...
Sonja Nießen, Hermann Ney
EMNLP
2008
13 years 9 months ago
Language and Translation Model Adaptation using Comparable Corpora
Traditionally, statistical machine translation systems have relied on parallel bi-lingual data to train a translation model. While bi-lingual parallel data are expensive to genera...
Matthew G. Snover, Bonnie J. Dorr, Richard M. Schw...
ACL
2012
11 years 10 months ago
Large-Scale Syntactic Language Modeling with Treelets
We propose a simple generative, syntactic language model that conditions on overlapping windows of tree context (or treelets) in the same way that n-gram language models condition...
Adam Pauls, Dan Klein
SIGDIAL
2010
13 years 5 months ago
Comparing Local and Sequential Models for Statistical Incremental Natural Language Understanding
Incremental natural language understanding is the task of assigning semantic representations to successively larger prefixes of utterances. We compare two types of statistical mod...
Silvan Heintze, Timo Baumann, David Schlangen