Enhancing Semantic Communication with Deep Generative Models -- An
ICASSP Special Session Overview
- URL: http://arxiv.org/abs/2309.02478v1
- Date: Tue, 5 Sep 2023 15:11:16 GMT
- Title: Enhancing Semantic Communication with Deep Generative Models -- An
ICASSP Special Session Overview
- Authors: Eleonora Grassucci, Yuki Mitsufuji, Ping Zhang, Danilo Comminiello
- Abstract summary: This ICASSP special session overview paper discloses the semantic communication challenges from the machine learning perspective.
It unveils how deep generative models will significantly enhance semantic communication frameworks.
It charts novel research pathways for the next generative semantic communication frameworks.
- Score: 25.314693624878053
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Semantic communication is poised to play a pivotal role in shaping the
landscape of future AI-driven communication systems. Its challenge of
extracting semantic information from the original complex content and
regenerating semantically consistent data at the receiver, possibly being
robust to channel corruptions, can be addressed with deep generative models.
This ICASSP special session overview paper discloses the semantic communication
challenges from the machine learning perspective and unveils how deep
generative models will significantly enhance semantic communication frameworks
in dealing with real-world complex data, extracting and exploiting semantic
information, and being robust to channel corruptions. Alongside establishing
this emerging field, this paper charts novel research pathways for the next
generative semantic communication frameworks.
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