Semantic Communication for the Internet of Sounds: Architecture, Design Principles, and Challenges

The Internet of Sounds (IoS) combines sound sensing, processing, and transmission techniques, enabling collaboration among diverse sound devices. To achieve a perceptual quality of sound synchronization in the IoS, it is necessary to precisely synchronize three critical factors: sound quality, timing, and behavior control. However, conventional bit-oriented communication, which focuses on bit reproduction, may not be able to fulfill these synchronization requirements under dynamic channel conditions. One promising approach to address the synchronization challenges of the IoS is relying on semantic communication (SC) that can capture and leverage the logical relationships in its source data. Consequently, in this article, we propose an IoS-centric SC framework with a transceiver design. The designed encoder extracts semantic information from diverse sources by leveraging neuro-symbolic AI and then transmits it to IoS listeners. For low-bandwidth scenarios, the encoder selectively distills important semantic information to reduce transmission latency for timing synchronization. At the receiver's end, the decoder reconstructs sounds and integrates them by leveraging semantic-aware reasoning, which helps achieve sound quality synchronization. Moreover, we present simulation results in a case study to validate the effectiveness of our framework. Finally, we explore several open issues on mathematical models, resource allocation, and cross-layer protocols.