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This paper investigates the scaling properties of Recurrent Neural Network Language Models (RNNLMs). We discuss how to train very large RNNs on GPUs and address the questions of how RNNLMs scale with respect to model size, training-set size, computational costs and memory. Our analysis shows that despite being more costly to train, RNNLMs obtain much lower(More)
Fourth-year undergraduate project in Group F, 2012/2013 I hereby declare that, except where specifically indicated, the work submitted herein is my own original work. Technical Abstract Adaptive Speaker Recognition Niranjani Prasad (CHR) Recent years have seen a significant rise in the interest in speech as a way of interacting with technology, from smart(More)
The management of invasive mechanical ventilation , and the regulation of sedation and anal-gesia during ventilation, constitutes a major part of the care of patients admitted to intensive care units. Both prolonged dependence on mechanical ventilation and premature extubation are associated with increased risk of complications and higher hospital costs,(More)
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