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
Latest papers with no code
Towards Emotion-aided Multi-modal Dialogue Act Classification
In this work, we address the role of \textit{both} multi-modality and emotion recognition (ER) in DAC.
Augmenting Small Data to Classify Contextualized Dialogue Acts for Exploratory Visualization
Our goal is to develop an intelligent assistant to support users explore data via visualizations.
Modeling Dialogue in Conversational Cognitive Health Screening Interviews
To facilitate the development of such an agent, we propose an annotation schema for assigning dialogue act labels to utterances in patient-interviewer conversations collected as part of a clinically-validated cognitive health screening task.
Chat or Learn: a Data-Driven Robust Question-Answering System
We present our choices of data sets for training and testing the components, and present the experimental results that helped us optimize the parameters of the chatbot.
Dialogue Act Classification in Team Communication for Robot Assisted Disaster Response
We present the results we obtained on the classification of dialogue acts in a corpus of human-human team communication in the domain of robot-assisted disaster response.
Dialogue Act Classification in Group Chats with DAG-LSTMs
In this paper, we introduce a new model architecture, directed-acyclic-graph LSTM (DAG-LSTM) for DA classification.
Identifying therapist conversational actions across diverse psychotherapeutic approaches
We propose to apply dialogue act classification to therapy transcripts, using a therapy-specific labeling scheme, in order to gain a high-level understanding of the flow of conversation in therapy sessions.
Improved Dynamic Memory Network for Dialogue Act Classification with Adversarial Training
Dialogue Act (DA) classification is a challenging problem in dialogue interpretation, which aims to attach semantic labels to utterances and characterize the speaker's intention.
A Dual-Attention Hierarchical Recurrent Neural Network for Dialogue Act Classification
Recognising dialogue acts (DA) is important for many natural language processing tasks such as dialogue generation and intention recognition.
Exploring Textual and Speech information in Dialogue Act Classification with Speaker Domain Adaptation
In spite of the recent success of Dialogue Act (DA) classification, the majority of prior works focus on text-based classification with oracle transcriptions, i. e. human transcriptions, instead of Automatic Speech Recognition (ASR)'s transcriptions.
