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» Word Importance Discrimination Using Context Information
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ICASSP
2010
IEEE
14 years 10 months ago
Discriminative training methods for language models using conditional entropy criteria
This paper addresses the problem of discriminative training of language models that does not require any transcribed acoustic data. We propose to minimize the conditional entropy ...
Jui-Ting Huang, Xiao Li, Alex Acero
CIVR
2008
Springer
138views Image Analysis» more  CIVR 2008»
14 years 11 months ago
MyPlaces: detecting important settings in a visual diary
We describe a novel approach to identifying specific settings in large collections of passively captured images corresponding to a visual diary. An algorithm developed for setting...
Michael Blighe, Noel E. O'Connor
ACL
1997
14 years 11 months ago
Incorporating Context Information for the Extraction of Terms
The information used for the extraction of terms can be considered as rather 'internal', i.e. coming from the candidate string itself. This paper presents the incorporat...
Katerina T. Frantzi
HT
2000
ACM
15 years 2 months ago
Clustering hypertext with applications to web searching
Clustering separates unrelated documents and groups related documents, and is useful for discrimination, disambiguation, summarization, organization, and navigation of unstructure...
Dharmendra S. Modha, W. Scott Spangler
COLING
2010
14 years 4 months ago
Unsupervised Discriminative Language Model Training for Machine Translation using Simulated Confusion Sets
An unsupervised discriminative training procedure is proposed for estimating a language model (LM) for machine translation (MT). An English-to-English synchronous context-free gra...
Zhifei Li, Ziyuan Wang, Sanjeev Khudanpur, Jason E...