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ACL
1997
14 years 11 months ago
Fertility Models for Statistical Natural Language Understanding
Several recent efforts in statistical natural language understanding (NLU) have focused on generating clumps of English words from semantic meaning concepts (Miller et al., 1995; ...
Stephen Della Pietra, Mark Epstein, Salim Roukos, ...
EMNLP
2010
14 years 7 months ago
A Fast Fertility Hidden Markov Model for Word Alignment Using MCMC
A word in one language can be translated to zero, one, or several words in other languages. Using word fertility features has been shown to be useful in building word alignment mo...
Shaojun Zhao, Daniel Gildea
SIGDIAL
2010
14 years 7 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
87
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HRI
2010
ACM
15 years 4 months ago
Toward understanding natural language directions
—Speaking using unconstrained natural language is an intuitive and flexible way for humans to interact with robots. Understanding this kind of linguistic input is challenging be...
Thomas Kollar, Stefanie Tellex, Deb Roy, Nicholas ...
83
Voted
NAACL
1994
14 years 10 months ago
Statistical Language Processing Using Hidden Understanding Models
This paper introduces a class of statistical mechanisms, called hidden understanding models, for natural language processing. Much of the framework for hidden understanding models...
Scott Miller, Richard M. Schwartz, Robert J. Bobro...