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)).
Datasets
Latest papers with no code
Task Selection and Assignment for Multi-modal Multi-task Dialogue Act Classification with Non-stationary Multi-armed Bandits
Our proposed method is significantly superior in terms of UAR and F1 to the single-task and multi-task baselines with p-values < 0. 05.
End-to-end spoken language understanding using joint CTC loss and self-supervised, pretrained acoustic encoders
It is challenging to extract semantic meanings directly from audio signals in spoken language understanding (SLU), due to the lack of textual information.
Does Informativeness Matter? Active Learning for Educational Dialogue Act Classification
Then, the study investigates how the AL methods can select informative samples to support DA classifiers in the AL sampling process.
A neural prosody encoder for end-ro-end dialogue act classification
Dialogue act classification (DAC) is a critical task for spoken language understanding in dialogue systems.
A Universality-Individuality Integration Model for Dialog Act Classification
Experiments were made over two most popular benchmark data sets SwDA and MRDA for dialogue act classification, and the results show that extracting the universalities and individualities between cues can more fully excavate the hidden information in the utterance, and improve the accuracy of automatic dialogue act recognition.
Speaker Clustering in Textual Dialogue with Utterance Correlation and Cross-corpus Dialogue Act Supervision
We propose a textual dialogue speaker clustering model, which groups the utterances of a multi-party dialogue without speaker annotations, so that the real speakers are identical inside each cluster.
Towards Building Automatic Medical Consultation System: Framework, Task and Dataset
In this paper, we propose two frameworks to support automatic medical consultation, namely doctor-patient dialogue understanding and diagnosis-oriented interaction.
Integrating User History into Heterogeneous Graph for Dialogue Act Recognition
Dialogue Act Recognition (DAR) is a challenging problem in Natural Language Understanding, which aims to attach Dialogue Act (DA) labels to each utterance in a conversation.
Two-level classification for dialogue act recognition in task-oriented dialogues
Dialogue act classification becomes a complex task when dealing with fine-grain labels.
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog
We obtain our representations with a hierarchical encoder based on transformer architectures, for which we extend two well-known pre-training objectives.