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We present a strategy to improve the quality of automatically generated cloze and open cloze questions which are used by the REAP tutoring system for assessment in the ill-defined domain of English as a Second Language vocabulary learning. Cloze and open cloze questions are fill-in-the-blank questions with and without multiple choice, respectively. The REAP(More)
This paper describes the University of Cambridge submission to the Eighth Workshop on Statistical Machine Translation. We report results for the Russian-English translation task. We use multiple segmentations for the Russian input language. We employ the Hadoop framework to extract rules. The decoder is HiFST, a hierarchical phrase-based de-coder(More)
Finding appropriate, authentic reading materials is a challenge for language instructors. The Web is a vast resource of texts, but most pages are not suitable for reading practice, and commercial search engines are not well suited to finding texts that satisfy pedagogical constraints such as reading level, length, text quality , and presence of target(More)
Data availability and distributed computing techniques have allowed statistical machine translation (SMT) researchers to build larger models. However, decoders need to be able to retrieve information efficiently from these models to be able to translate an input sentence or a set of input sentences. We introduce an easy to implement and general purpose(More)
This paper describes the early stages of porting REAP, a tutoring system for vocabulary learning, to European Portuguese. Students learn from authentic materials, on topics of their preference. A large number of linguistic resources and filtering tools have already been integrated into the ported version. We modified the current system to also target oral(More)
We report on investigations into hierarchical phrase-based translation grammars based on rules extracted from posterior distributions over alignments of the parallel text. Rather than restrict rule extraction to a single alignment , such as Viterbi, we instead extract rules based on posterior distributions provided by the HMM word-to-word alignment model.(More)
We report on the observation of controllable phase separation in a dual-species Bose-Einstein condensate with 85Rb and 87Rb. Interatomic interactions between the different components determine the miscibility of the two quantum fluids. In our experiments, we can clearly observe immiscible behavior via a dramatic spatial separation of the two species.(More)
We describe a method to semi-automatically generate incorrect choices, or distractors, for cloze (fill-in-the-blank) questions. We generated distractors aimed at revealing what type of misunderstanding a student was having. English as a Second Language learners answered a series of cloze questions that presented distractors generated by our method. We(More)
We report on measurements of the excitation spectrum of a strongly interacting Bose-Einstein condensate. A magnetic-field Feshbach resonance is used to tune atom-atom interactions in the condensate and to reach a regime where quantum depletion and beyond mean-field corrections to the condensate chemical potential are significant. We use two-photon Bragg(More)
This paper describes the Cambridge University Engineering Department submission to the Fifth Workshop on Statistical Machine Translation. We report results for the French-English and Spanish-English shared translation tasks in both directions. The CUED system is based on HiFST, a hierarchical phrase-based decoder implemented using weighted finite-state(More)