Papers Dialogue Act Classification
“Dialogue Act Classification” 태그가 달린 논문 65편 · 필터 해제
Learning LLM Preference over Intra-Dialogue Pairs: A Framework for Utterance-level Understandings
Large language models (LLMs) have demonstrated remarkable capabilities in handling complex dialogue tasks without requiring use case-specific fine-tuning. However, analyzing live dialogues in real-time necessitates low-l…
Dialogue Act ClassificationDialogue State TrackingIntent DetectionLow-latency processingHierarchical Fusion for Online Multimodal Dialog Act Classification
We propose a framework for online multimodal dialog act (DA) classification based on raw audio and ASR-generated transcriptions of current and past utterances. Existing multimodal DA classification approaches are limited…
ClassificationDialog Act ClassificationDialogue Act ClassificationInterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanations
While recently developed NLP explainability methods let us open the black box in various ways (Madsen et al., 2022), a missing ingredient in this endeavor is an interactive tool offering a conversational interface. Such …
Dialogue Act ClassificationHate Speech DetectionQuestion AnsweringTask Selection and Assignment for Multi-modal Multi-task Dialogue Act Classification with Non-stationary Multi-armed Bandits
Multi-task learning (MTL) aims to improve the performance of a primary task by jointly learning with related auxiliary tasks. Traditional MTL methods select tasks randomly during training. However, both previous studies …
Dialogue Act ClassificationMulti-Armed BanditsMulti-Task LearningThompson SamplingEnd-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. Popular end-to-end (E2E) SLU models utilize sequence-to-sequence …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Dialogue Act Classificationspeech-recognition+2NatCS: Eliciting Natural Customer Support Dialogues
Despite growing interest in applications based on natural customer support conversations, there exist remarkably few publicly available datasets that reflect the expected characteristics of conversations in these setting…
Dialogue Act ClassificationHierarchical Dialogue Understanding with Special Tokens and Turn-level Attention
Compared with standard text, understanding dialogue is more challenging for machines as the dynamic and unexpected semantic changes in each turn. To model such inconsistent semantics, we propose a simple but effective Hi…
Dialogue Act ClassificationDialogue UnderstandingEmotion RecognitionRelation ExtractionDoes Informativeness Matter? Active Learning for Educational Dialogue Act Classification
Dialogue Acts (DAs) can be used to explain what expert tutors do and what students know during the tutoring process. Most empirical studies adopt the random sampling method to obtain sentence samples for manual annotatio…
Active LearningDialogue Act ClassificationInformativenessSentenceDOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents
In the real world, autonomous driving agents navigate in highly dynamic environments full of unexpected situations where pre-trained models are unreliable. In these situations, what is immediately available to vehicles i…
Autonomous DrivingDialogue Act ClassificationRobot NavigationVision and Language NavigationSpeaker Clustering in Textual Dialogue with Pairwise Utterance Relation and Cross-corpus Dialogue Act Supervision
We propose a speaker clustering model for textual dialogues, which groups the utterances of a multi-party dialogue without speaker annotations, so that the actual speakers are identical inside each cluster. We find that,…
ClusteringCross-corpusDialogue Act ClassificationLanguage Modeling+4Increasing Robustness for Cross-domain Dialogue Act Classification on Social Media Data
Automatically detecting the intent of an utterance is important for various downstream natural language processing tasks. This task is also called Dialogue Act Classification (DAC) and was primarily researched on spoken …
Dialogue Act ClassificationLexical NormalizationLearning Dialogue Representations from Consecutive Utterances
Learning high-quality dialogue representations is essential for solving a variety of dialogue-oriented tasks, especially considering that dialogue systems often suffer from data scarcity. In this paper, we introduce Dial…
Contrastive LearningConversational Question AnsweringConversational Response SelectionDialogue Act Classification+14A 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. Prosodic features such as energy and pitch have been shown to be useful for DAC. Despite their importance, littl…
Dialogue Act ClassificationSpoken Language UnderstandingA 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. In this article, we propose two frameworks to support automatic m…
Dialogue Act ClassificationDialogue UnderstandingMedical Report Generationnamed-entity-recognition+2A Universality-Individuality Integration Model for Dialog Act Classification
Dialog Act (DA) reveals the general intent of the speaker utterance in a conversation. Accurately predicting DAs can greatly facilitate the development of dialog agents. Although researchers have done extensive research …
ClassificationDialog Act ClassificationDialogue Act ClassificationDiversitySpeaker 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. We find that, even w…
ClusteringCross-corpusDialogue Act ClassificationLanguage Modeling+1Towards 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. A new medical dialogue dataset with multi-level fine-gr…
Dialogue Act ClassificationDialogue UnderstandingMedical Named Entity RecognitionMedical Report Generation+3Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling Conversations
The onset of the COVID-19 pandemic has brought the mental health of people under risk. Social counselling has gained remarkable significance in this environment. Unlike general goal-oriented dialogues, a conversation bet…
Dialogue Act ClassificationSentence 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…
ClassificationDialog Act ClassificationDialogue Act ClassificationSentence+1Speaker Turn Modeling for Dialogue Act Classification
Dialogue Act (DA) classification is the task of classifying utterances with respect to the function they serve in a dialogue. Existing approaches to DA classification model utterances without incorporating the turn chang…
ClassificationDialogue Act Classification