  Semantic communication, when examined through the lens of joint
source-channel coding (JSCC), maps source messages directly into channel input
symbols, where the measure of success is defined by end-to-end distortion
rather than traditional metrics such as block error rate. Previous studies have
shown significant improvements achieved through deep learning (DL)-driven JSCC
compared to traditional separate source and channel coding. However, JSCC is
impractical in existing communication networks, where application and network
providers are typically different entities connected over general-purpose
TCP/IP links. In this paper, we propose designing the source and channel
mappings separately and sequentially via a novel multi-level reliability
interface. This conceptual interface enables semi-JSCC at both the learned
source and channel mappers and achieves many of the gains observed in existing
DL-based JSCC work (which would require a fully joint design between the
application and the network), such as lower end-to-end distortion and graceful
degradation of distortion with channel quality. We believe this work represents
an important step towards realizing semantic communications in wireless
networks.
