Using Paraphrases and Lexical Semantics to Improve the Accuracy and the Robustness of Supervised Models in Situated Dialogue Systems
Abstract
This paper explores to what extent lemmatisation, lexical resources, distributional semantics and paraphrases can increase the accuracy of supervised models for dialogue management. The results suggest that each of these factors can help improve performance but that the impact will vary depending on their combination and on the evaluation mode.
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