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 ...
Long-term search history contains rich information about a user's search preferences. In this paper, we study statistical language modeling based methods to mine contextual i...
In recent years statistical word alignment models have been widely used for various Natural Language Processing (NLP) problems. In this paper we describe a platform independent and...
GeoCLEF is an evaluation initiative for testing queries with a geographic specification in large set of text documents. GeoCLEF ran a regular track for the third time within the C...
Thomas Mandl, Paula Carvalho, Giorgio Maria Di Nun...
We present a novel framework for word alignment that incorporates synonym knowledge collected from monolingual linguistic resources in a bilingual probabilistic model. Synonym inf...