Natural Language Processing for Conversational AI
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 5755
Special Issue Editors
Interests: conversational AI; dialogue management; social interactions; reinforcement learning
Interests: dialogue systems; artificial intelligence, machine learning, reinforcement learning
Interests: natural language understanding; spoken dialog systems
Special Issue Information
Dear Colleagues,
Conversational AI has seen great progress in recent years, but many challenges still remain to be solved. The more we try to model human–human interaction, the more we realize that conversational AI is an interdisciplinary subject, involving fields that range from machine learning to psychology and sociology.
Many initiatives to advance the state of the art were started in different research communities, including the Dialogue State Tracking Challenges (that transformed into the Dialogue Systems Technology Challenges), the NeurIPS Conversational Intelligence Challenge live competition, and the Amazon Alexa prize competition. However, various fields within the NLP community, such as semantic parsing, coreference resolution, sentiment analysis, question answering, or machine reading comprehension, among others, have seldom been evaluated or applied in the context of conversational AI.
This special session aims to bring together NLP researchers and practitioners from different fields, alongside experts in speech and machine learning, to advance the current state-of-the-art, share insights and challenges, and bridge the gap between academic research and real-world product deployment.
Topics of interest include:
- Language Understanding (NLU/SLU)
- Language Generation
- Dialogue State Tracking
- Policy Optimization (Supervised/Reinforced)
- Dialogue Evaluation
- Dialogue Data Collection/Datasets
- End-to-End Dialogue Modeling
- Multimodal Dialogue
- Discourse Modeling
- Coreference Resolution
- Dialogue Representation Learning
- Conversational AI Deployment
- User Modeling
- Learning from User Feedback
- Human-in-the-loop Dialogue
Dr. Alexandros Papangelis
Dr. Elnaz Nouri
Dr. Bing Liu
Dr. Yun-Nung (Vivian) Chen
Guest Editors
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Keywords
- natural language processing
- conversational AI
- spoken dialogue systems
- human–computer interaction
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