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 ...
We describe a novel approach to identifying specific settings in large collections of passively captured images corresponding to a visual diary. An algorithm developed for setting...
The information used for the extraction of terms can be considered as rather 'internal', i.e. coming from the candidate string itself. This paper presents the incorporat...
Clustering separates unrelated documents and groups related documents, and is useful for discrimination, disambiguation, summarization, organization, and navigation of unstructure...
An unsupervised discriminative training procedure is proposed for estimating a language model (LM) for machine translation (MT). An English-to-English synchronous context-free gra...
Zhifei Li, Ziyuan Wang, Sanjeev Khudanpur, Jason E...