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Neural approaches to conversational AI
This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …
few years. We group conversational systems into three categories:(1) question answering …
A survey on deep reinforcement learning for audio-based applications
Deep reinforcement learning (DRL) is poised to revolutionise the field of artificial intelligence
(AI) by endowing autonomous systems with high levels of understanding of the real world …
(AI) by endowing autonomous systems with high levels of understanding of the real world …
Sentiment adaptive end-to-end dialog systems
Rubicon: Rubric-based evaluation of domain-specific human ai conversations
Evaluating conversational assistants, such as GitHub Copilot Chat, poses a significant
challenge for tool builders in the domain of Software Engineering. These assistants rely on …
challenge for tool builders in the domain of Software Engineering. These assistants rely on …
Emotion-sensitive deep dyna-q learning for task-completion dialogue policy learning
In recent years, task-oriented dialogue systems have received extensive attention from
academia and industry. Training a dialogue agent through reinforcement learning is often …
academia and industry. Training a dialogue agent through reinforcement learning is often …
Improving interaction quality estimation with BiLSTMs and the impact on dialogue policy learning
S Ultes - arxiv preprint arxiv:2001.07615, 2020 - arxiv.org
Learning suitable and well-performing dialogue behaviour in statistical spoken dialogue
systems has been in the focus of research for many years. While most work which is based …
systems has been in the focus of research for many years. While most work which is based …