This paper proposes a model using associative processors (APs) for real-time spoken language translation. Spoken language translation requires (1) an accurate translation and (2) ...
Temporal expressions, such as between 1992 and 2000, are frequent across many kinds of documents. Text retrieval, though, treats them as common terms, thus ignoring their inherent...
Irem Arikan, Srikanta J. Bedathur, Klaus Berberich
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 ...
The approach of using passage-level evidence for document retrieval has shown mixed results when it is applied to a variety of test beds with different characteristics. One main r...
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...