Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives

September 21, 2018 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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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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