Abstract: We present a new approach to dynamically create and manage different language models to be used on a spoken dialogue system. We apply an interpolation based approach, using several measures obtained by the Dialogue Manager to decide what LM the system will interpolate and also to estimate the interpolation weights. We propose to use not only semantic information (the concepts extracted from each recognized utterance), but also information obtained by the dialogue manager module (DM), that is, the objectives orgoals the user wants to fulfill, an...
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Topics: 
Speech recognition
Natural language processing
Artificial intelligence