Title
Local Methods for On-Demand Out-of-Vocabulary Word Retrieval
Abstract
Most of the Web-based methods for lexicon augmenting consist in capturing global semantic features of the targeted domain in order to collect relevant documents from the Web. We suggest that the local context of the out-of-vocabulary (OOV) words contains relevant information on the OOV words. With this information, we propose to use the Web to build locally-augmented lexicons which are used in a final local decoding pass. First, an automatic web based OOV word detection method is proposed. Then, we demonstrate the relevance of the Web for the OOV word retrieval. Different methods are proposed to retrieve the hypothesis words. We finally retrieve about 26% of the OOV words with a lexicon increase of less than 1000 words using the reference context.
Year
Venue
Field
2008
SIXTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, LREC 2008
On demand,Information retrieval,Computer science,Speech recognition,Lexicon,Natural language processing,Artificial intelligence,Decoding methods,Web application,Out of vocabulary
DocType
Citations 
PageRank 
Conference
1
0.39
References 
Authors
7
3
Name
Order
Citations
PageRank
Stanislas Oger1142.55
Georges Linares28719.73
Frédéric Béchet339747.77