Modèles Informatiques du Langage et de la Cognition - MILC
Artificial Intelligence Group
Computer Science Department
Français
Research
Papers
Home
Jacques HAN
Ph.D. Student
Biography
Tree substitution grammars and syntatic analysis through sampling:
application to the automated acquisition of probabilistic grammars.
One of the important issues that dominate current research work in parsing
and language modeling is the efficient integration of naturally occurring
linguistic material (corpora, treebanks, ...) in the design of natural
language parsers for specific applications.
Simple high-coverage methods such as n-gram models miss the higher-order
regularities required for reliable analysis, while laboriously hand-crafted
computational grammars are often incomplete and ambiguous. Therefore, the
objective of our research is to study how to combine explicite linguistic
knowledge (e.g. predefined syntactic trees) and probabilistic techniques
to design improved automated acquisition methods of natural language
parsers.
In particular, we will concentrate on the acquisition of probabilistic
parsers based on Monte-Carlo techniques and tree-substitution grammars.
Thesis directors : Martin RAJMAN
Research Group : MILC
Laboratory : Computer Science Department, TELECOM Paris
Intended examination date : May 1998
- (Rajman 95b)
M. RAJMAN,
J. HAN,
" Prise en compte de contraintes syntaxiques dans le cadre d'un
système de reconnaissance de la parole", 2nde
conférence sur le Traitement Automatique du Langage Naturel
(TALN95), Marseille, juin 1995
Jacques HAN (han@inf.enst.fr)
Research
Papers