Edge Speech Application

Edge speech applications aim to perform speech processing directly on resource-constrained devices, minimizing data transfer and latency. Current research focuses on improving model efficiency through techniques like model compression (quantization, pruning), decentralized federated learning to handle heterogeneous devices and data, and the use of novel architectures such as gated compression layers to dynamically regulate computation. These advancements are crucial for enabling always-on, low-power speech recognition and other speech-based tasks on edge devices, impacting fields like IoT and mobile computing.