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Found 2 papers, 2 papers with code
Sentence encoding for Dialogue Act classification
In this study, we investigate the process of generating single-sentence representations for the purpose of Dialogue Act (DA) classification, including several aspects of text pre-processing and input representation which are often overlooked or underreported within the literature, for example, the number of words to keep in the vocabulary or input sequences.
Probabilistic Word Association for Dialogue Act Classification with Recurrent Neural Networks
The identification of Dialogue Act’s (DA) is an important aspect in determining the meaning of an utterance for many applications that require natural language understanding, and recent work using recurrent neural networks (RNN) has shown promising results when applied to the DA classification problem.
Ranked #1 on
Dialog Act Classification
on Switchboard dialogue act corpus
(Accuracy (%) metric)
