Language model (LM) adaptation is important for both speech and language processing. It is often achieved by combining a generic LM with a topic-specific model that is more releva...
This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity...
Language models for speech recognition tend to be brittle across domains, since their performance is vulnerable to changes in the genre or topic of the text on which they are trai...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Background: When term ambiguity and variability are very high, dictionary-based Named Entity Recognition (NER) is not an ideal solution even though large-scale terminological reso...
Yutaka Sasaki, Yoshimasa Tsuruoka, John McNaught, ...