Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives
September 21, 2018 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Jing Han, Zixing Zhang, Nicholas Cummins, Bjรถrn Schuller
arXiv ID
1809.08927
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.HC
Citations
64
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Over the past few years, adversarial training has become an extremely active research topic and has been successfully applied to various Artificial Intelligence (AI) domains. As a potentially crucial technique for the development of the next generation of emotional AI systems, we herein provide a comprehensive overview of the application of adversarial training to affective computing and sentiment analysis. Various representative adversarial training algorithms are explained and discussed accordingly, aimed at tackling diverse challenges associated with emotional AI systems. Further, we highlight a range of potential future research directions. We expect that this overview will help facilitate the development of adversarial training for affective computing and sentiment analysis in both the academic and industrial communities.
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