边缘设备算力不够？这篇论文用云端模型来帮忙，做语音增强效果好还省算力，搞可穿戴的可以看看。
该论文提出一种云边协同的语音增强框架，针对可穿戴设备低延迟、低算力的约束，利用云端模型辅助边缘模型。框架包含三项技术：延迟服务器输出作为额外输入、逐层特征提升以及协同多通道维纳滤波。实验表明，该框架相比纯边缘基线显著提升性能，且额外计算开销极小。
Cloud-Boosted Low-Compute Multi-Channel Speech Enhancement
Low-latency, low-compute speech enhancement is essential for wearable devices with real-time communication requirements, but strict computational constraints significantly limit on-device performance. Knowledge Boosting has been proposed as an effective approach to improve edge model performance by leveraging a more capable server-side model, but performance gains for speech enhancement have been limited. We propose a collaborative framework incorporating three techniques: (1) delayed server output as additional input, (2) layerwise feature boosting that transfers intermediate server representations to guide edge inference, and (3) collaborative multichannel Wiener filtering, which fuses weighted covariance matrices estimated from both server and edge models for improved beamforming. Experimental results demonstrate that the proposed collaborative framework significantly outperforms the edge-only baseline with minimal additional computational overhead.