We present a machine learning approach to evaluating the wellformedness of output of a machine translation system, using classifiers that learn to distinguish human reference tran...
Simon Corston-Oliver, Michael Gamon, Chris Brocket...
This paper presents MISTRAL, an open source statistical machine translation decoder dedicated to spoken language translation. While typical machine translation systems take a writ...
We demonstrate a web-based machine translation environment that can be improved in terms of accuracy and scope through online collaboration by users. The environment leverages the...
A Co-Designed Virtual Machine allows designers to implement a processor via a combination of hardware and software. Dynamic binary translation converts code written for a conventi...
Conventional mutual information (MI)-based registration using pixel intensities is time-consuming and ignores spatial information, which can lead to misalignment. We propose a met...