Nishitha Guntakandla
2018
Annotating Reflections for Health Behavior Change Therapy
Nishitha Guntakandla
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Rodney Nielsen
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
2016
Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network
Hamed Khanpour
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Nishitha Guntakandla
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Rodney Nielsen
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
In this study, we applied a deep LSTM structure to classify dialogue acts (DAs) in open-domain conversations. We found that the word embeddings parameters, dropout regularization, decay rate and number of layers are the parameters that have the largest effect on the final system accuracy. Using the findings of these experiments, we trained a deep LSTM network that outperforms the state-of-the-art on the Switchboard corpus by 3.11%, and MRDA by 2.2%.
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