Dialogue Act Classification
23 papers with code • 5 benchmarks • 8 datasets
Dialogue act classification is the task of classifying an utterance with respect to the function it serves in a dialogue, i.e. the act the speaker is performing. Dialogue acts are a type of speech acts (for Speech Act Theory, see Austin (1975) and Searle (1969)).
Benchmarks
These leaderboards are used to track progress in Dialogue Act Classification
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Datasets
Doc2Dial
CPED
Emotional Dialogue Acts
Most implemented papers
Guiding attention in Sequence-to-sequence models for Dialogue Act prediction
The task of predicting dialog acts (DA) based on conversational dialog is a key component in the development of conversational agents.
Contextual Dialogue Act Classification for Open-Domain Conversational Agents
emory-irlab/CDAC
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Furthermore, our results show that fine-tuning the CDAC model on a small sample of manually labeled human-machine conversations allows CDAC to more accurately predict dialogue acts in real users' conversations, suggesting a promising direction for future improvements.
Handling Class Imbalance in Low-Resource Dialogue Systems by Combining Few-Shot Classification and Interpolation
Utterance classification performance in low-resource dialogue systems is constrained by an inevitably high degree of data imbalance in class labels.
Speaker Turn Modeling for Dialogue Act Classification
zaghe568/speak-turn-emb-dialog-act-clf
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Findings (EMNLP) 2021
Dialogue Act (DA) classification is the task of classifying utterances with respect to the function they serve in a dialogue.
Sentence encoding for Dialogue Act classification
NathanDuran/Sentence-Encoding-for-DA-Classification
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Natural Language Engineering 2021
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.
Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling Conversations
lcs2-iiitd/sparta_wsdm2022
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We identify the requirement of such conversation and propose twelve domain-specific dialogue-act (DAC) labels.
A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasets
In recent years, interest has arisen in using machine learning to improve the efficiency of automatic medical consultation and enhance patient experience.
Learning Dialogue Representations from Consecutive Utterances
amazon-research/dse
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NAACL 2022
In this paper, we introduce Dialogue Sentence Embedding (DSE), a self-supervised contrastive learning method that learns effective dialogue representations suitable for a wide range of dialogue tasks.
DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents
To this end, we introduce Dialogue On the ROad To Handle Irregular Events (DOROTHIE), a novel interactive simulation platform that enables the creation of unexpected situations on the fly to support empirical studies on situated communication with autonomous driving agents.
Hierarchical Dialogue Understanding with Special Tokens and Turn-level Attention
shawx825/hidialog
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Tiny Papers @ ICLR 2023
We evaluate our model on various dialogue understanding tasks including dialogue relation extraction, dialogue emotion recognition, and dialogue act classification.
