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Deep learning is revolutionizing speech and natural language technologies since it is offering an effective way to train systems and obtaining significant improvements. The main advantage of deep learning is that, by developing the right architecture, the system automatically learns features from data without the need of explicitly designing them. This machine learning perspective is conceptually...
The effective integration of MT technology into computer-assisted translation tools is a challenging topic both for academic research and the translation industry. In particular, professional translators consider the ability of MT systems to adapt to the feedback provided by them to be crucial. In this paper, we propose an adaptation scheme to tune a statistical MT system to a translation project...
A general approach for integrating different acoustic feature sets and acoustic models is presented. A strategy for using a feature set as a reference and for scheduling the execution of other feature sets is introduced. The strategy is based on the introduction of feature variability states. Each phoneme of a word hypothesis is assigned one of such states. The probability that a word hypothesis is...
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