Espnet-slu: Advancing spoken language understanding through espnet
As Automatic Speech Processing (ASR) systems are getting better, there is an increasing
interest of using the ASR output to do downstream Natural Language Processing (NLP) …
interest of using the ASR output to do downstream Natural Language Processing (NLP) …
Modeling feedback in interaction with conversational agents—a review
Intelligent agents interacting with humans through conversation (such as a robot, embodied
conversational agent, or chatbot) need to receive feedback from the human to make sure …
conversational agent, or chatbot) need to receive feedback from the human to make sure …
Dialogbert: Discourse-aware response generation via learning to recover and rank utterances
Recent advances in pre-trained language models have significantly improved neural
response generation. However, existing methods usually view the dialogue context as a …
response generation. However, existing methods usually view the dialogue context as a …
Dialogue act classification with context-aware self-attention
V Raheja, J Tetreault - arXiv preprint arXiv:1904.02594, 2019 - arxiv.org
Recent work in Dialogue Act classification has treated the task as a sequence labeling
problem using hierarchical deep neural networks. We build on this prior work by leveraging …
problem using hierarchical deep neural networks. We build on this prior work by leveraging …
A context-based approach for dialogue act recognition using simple recurrent neural networks
Dialogue act recognition is an important part of natural language understanding. We
investigate the way dialogue act corpora are annotated and the learning approaches used …
investigate the way dialogue act corpora are annotated and the learning approaches used …
HAM-GNN: A hierarchical attention-based multi-dimensional edge graph neural network for dialogue act classification
Dialogue act (DA) analysis is crucial for developing natural conversational systems and
dialogue generation. Modelling DA labels at the utterance-level requires contextual and …
dialogue generation. Modelling DA labels at the utterance-level requires contextual and …
Predicting Client Emotions and Therapist Interventions in Psychotherapy Dialogues
T Mayer, N Warikoo, A Eliassaf… - Proceedings of the …, 2024 - aclanthology.org
Abstract Natural Language Processing (NLP) can advance psychotherapy research by
scaling up therapy dialogue analysis as well as by allowing researchers to examine client …
scaling up therapy dialogue analysis as well as by allowing researchers to examine client …
What helps transformers recognize conversational structure? Importance of context, punctuation, and labels in dialog act recognition
Dialog acts can be interpreted as the atomic units of a conversation, more fine-grained than
utterances, characterized by a specific communicative function. The ability to structure a …
utterances, characterized by a specific communicative function. The ability to structure a …
Speaker-change aware CRF for dialogue act classification
Recent work in Dialogue Act (DA) classification approaches the task as a sequence labeling
problem, using neural network models coupled with a Conditional Random Field (CRF) as …
problem, using neural network models coupled with a Conditional Random Field (CRF) as …
Self-governing neural networks for on-device short text classification
S Ravi, Z Kozareva - Proceedings of the 2018 Conference on …, 2018 - aclanthology.org
Deep neural networks reach state-of-the-art performance for wide range of natural language
processing, computer vision and speech applications. Yet, one of the biggest challenges is …
processing, computer vision and speech applications. Yet, one of the biggest challenges is …