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We introduce a Bayesian approach for the adaptation of the log-linear weights present in state-of-the-art statistical machine translation systems. Typically, these weights are estimated by optimising a given translation quality criterion, taking only into account a certain set of development data (e.g., the adaptation data). In this article, we show that the Bayesian framework provides appropriate...
One of the most promising approaches to machine translation consists in formulating the problem by means of a pattern recognition approach. By doing so, there are some tasks in which online adaptation is needed in order to adapt the system to changing scenarios. In the present work, we perform an exhaustive comparison of four online learning algorithms when combined with two adaptation strategies...
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