Papers with dialogue act recognition datasets

1 papers
Learning Spoken Language Representations with Neural Lattice Language Modeling (2020.acl-main)

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Challenge: Existing methods for pretraining language models do not consider spoken language properties.
Approach: They propose a framework that trains neural lattice language models to provide contextualized representations for spoken language understanding tasks.
Outcome: The proposed framework outperforms baselines on spoken inputs on intent detection and dialogue act recognition datasets.

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