Adaptive Edge-Cloud Inference for Speech-to-Action Systems Using ASR and Large Language Models

This article likely discusses a research paper focusing on optimizing the performance of speech-to-action systems. It explores the use of Automatic Speech Recognition (ASR) and Large Language Models (LLMs) in a distributed edge-cloud environment. The core focus is on adaptive inference, suggesting techniques to dynamically allocate computational resources between edge devices and the cloud to improve efficiency and reduce latency.