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.

通过引入内容生成层，将人工智能生成内容 (AIGC) 与语义通讯 (SemCom) 结合起来，提供了清晰的 AIGC 与 SemCom 之间互动产生有意义和有效内容的概念模型，并提出了一种基于 AIGC 技术的语义信息编码器和解码器的新框架，以优化 AIGC 服务的语义提取和评估指标，从而适应不同类型的内容生成、所需质量和语义信息使用。通过使用深度 Q 网络 (DQN)，展示了对优化问题的可行性和收敛特性的有益见解。