Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potential, especially when integrating with semantic communication (SemCom). In this paper, a novel comprehensive conceptual model for the integration of AIGC and SemCom is developed. Particularly, a content generation level is introduced on top of the semantic level that provides a clear outline of how AIGC and SemCom interact with each other to produce meaningful and effective content. Moreover, a novel framework that employs AIGC technology is proposed as an encoder and decoder for semantic information, considering the joint optimization of semantic extraction and evaluation metrics tailored to AIGC services. The framework can adapt to different types of content generated, the required quality, and the semantic information utilized. By employing a Deep Q Network (DQN), a case study is presented that provides useful insights into the feasibility of the optimization problem and its convergence characteristics.

翻译：人工智能生成内容（AIGC）服务在数字内容创建领域具有巨大潜力。AIGC的独特能力，例如基于极少量输入生成内容，展现出广阔前景，特别是在与语义通信（SemCom）结合时。本文提出了一种新颖的、综合性的AIGC与SemCom集成概念模型。具体而言，在语义层之上引入了一个内容生成层，清晰勾勒了AIGC与SemCom如何相互协作以生成有意义且有效的内容。此外，本文提出了一种采用AIGC技术的新颖框架，该框架将AIGC作为语义信息的编码器和解码器，并考虑了针对AIGC服务的语义提取与评估指标的联合优化。该框架能够适应不同类型生成内容、所需质量以及所利用的语义信息。通过采用深度Q网络（DQN），本文呈现了一个案例研究，为优化问题的可行性及其收敛特性提供了有价值的见解。