In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
This paper presents a semantic confidence measure that aims to predict the relevance of automatic transcripts for a task of Spoken Document Retrieval (SDR). The proposed predicti...
Word prediction performed by language models has an important role in many tasks as e.g. word sense disambiguation, speech recognition, hand-writing recognition, query spelling an...
This paper describes work within the NIST Text REtrieval Conference (TREC) over the last three years in designing and implementing evaluations of Spoken Document Retrieval (SDR) t...
John S. Garofolo, Cedric G. P. Auzanne, Ellen M. V...
In this paper two aspects of generating and using phonetic Arabic dictionaries are described. First, the use of single pronunciation acoustic models in the context of Arabic large...
Frank Diehl, Mark J. F. Gales, Marcus Tomalin, Phi...