Papers with utterance-level representation learning methods

1 papers
Dialogue Act Classification with Context-Aware Self-Attention (N19-1)

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Challenge: Recent work in Dialogue Act classification has treated the task as a sequence labeling problem using hierarchical deep neural networks.
Approach: They propose a hierarchical deep neural network to model different levels of utterance and dialogue act semantics and use contextual dependencies to improve performance.
Outcome: The proposed model improves on the Switchboard Dialogue Act Corpus while maintaining high accuracy.

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