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arXiv · 1510.03753

Improved Deep Learning Baselines for Ubuntu Corpus Dialogs

Rudolf Kadlec·Martin Schmid·Jan Kleindienst
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Abstract

This paper presents results of our experiments for the next utterance ranking on the Ubuntu Dialog Corpus -- the largest publicly available multi-turn dialog corpus. First, we use an in-house implementation of previously reported models to do an independent evaluation using the same data. Second, we evaluate the performances of various LSTMs, Bi-LSTMs and CNNs on the dataset. Third, we create an ensemble by averaging predictions of multiple models. The ensemble further improves the performance and it achieves a state-of-the-art result for the next utterance ranking on this dataset. Finally, we discuss our future plans using this corpus.

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BibTeXRIS

Rudolf Kadlec, Martin Schmid, Jan Kleindienst. 2015-11-03. Improved Deep Learning Baselines for Ubuntu Corpus Dialogs. https://arxiv.org/abs/1510.03753

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