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» Improving Language Models by Clustering Training Sentences
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ICASSP
2011
IEEE
12 years 11 months ago
Multi-class Model M
Model M, a novel class-based exponential language model, has been shown to significantly outperform word n-gram models in state-of-the-art machine translation and speech recognit...
Ahmad Emami, Stanley F. Chen
CEC
2010
IEEE
13 years 9 months ago
Evolving natural language grammars without supervision
Unsupervised grammar induction is one of the most difficult works of language processing. Its goal is to extract a grammar representing the language structure using texts without a...
Lourdes Araujo, Jesus Santamaria
PROCEDIA
2010
105views more  PROCEDIA 2010»
13 years 6 months ago
Improvement of parallelization efficiency of batch pattern BP training algorithm using Open MPI
The use of tuned collective’s module of Open MPI to improve a parallelization efficiency of parallel batch pattern back propagation training algorithm of a multilayer perceptron...
Volodymyr Turchenko, Lucio Grandinetti, George Bos...
NAACL
2007
13 years 9 months ago
Direct Translation Model 2
This paper presents a maximum entropy machine translation system using a minimal set of translation blocks (phrase-pairs). While recent phrase-based statistical machine translatio...
Abraham Ittycheriah, Salim Roukos
ACL
2003
13 years 9 months ago
Improved Source-Channel Models for Chinese Word Segmentation
This paper presents a Chinese word segmentation system that uses improved sourcechannel models of Chinese sentence generation. Chinese words are defined as one of the following fo...
Jianfeng Gao, Mu Li, Changning Huang