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» Improving Language Models by Clustering Training Sentences
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EMNLP
2009
13 years 5 months ago
Sinuhe - Statistical Machine Translation using a Globally Trained Conditional Exponential Family Translation Model
We present a new phrase-based conditional exponential family translation model for statistical machine translation. The model operates on a feature representation in which sentenc...
Matti Kääriäinen
EMNLP
2010
13 years 5 months ago
Training Continuous Space Language Models: Some Practical Issues
Using multi-layer neural networks to estimate the probabilities of word sequences is a promising research area in statistical language modeling, with applications in speech recogn...
Hai Son Le, Alexandre Allauzen, Guillaume Wisniews...
ACL
2001
13 years 9 months ago
Multi-Class Composite N-gram Language Model for Spoken Language Processing Using Multiple Word Clusters
In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect traini...
Hirofumi Yamamoto, Shuntaro Isogai, Yoshinori Sagi...
EMNLP
2009
13 years 5 months ago
Re-Ranking Models Based-on Small Training Data for Spoken Language Understanding
The design of practical language applications by means of statistical approaches requires annotated data, which is one of the most critical constraint. This is particularly true f...
Marco Dinarelli, Alessandro Moschitti, Giuseppe Ri...
ACL
2012
11 years 10 months ago
Crosslingual Induction of Semantic Roles
We argue that multilingual parallel data provides a valuable source of indirect supervision for induction of shallow semantic representations. Specifically, we consider unsupervi...
Ivan Titov, Alexandre Klementiev