  Speech bandwidth extension (BWE) has demonstrated promising performance in
enhancing the perceptual speech quality in real communication systems. Most
existing BWE researches primarily focus on fixed upsampling ratios,
disregarding the fact that the effective bandwidth of captured audio may
fluctuate frequently due to various capturing devices and transmission
conditions. In this paper, we propose a novel streaming adaptive bandwidth
extension solution dubbed BAE-Net, which is suitable to handle the
low-resolution speech with unknown and varying effective bandwidth. To address
the challenges of recovering both the high-frequency magnitude and phase speech
content blindly, we devise a dual-stream architecture that incorporates the
magnitude inpainting and phase refinement. For potential applications on edge
devices, this paper also introduces BAE-NET-lite, which is a lightweight,
streaming and efficient framework. Quantitative results demonstrate the
superiority of BAE-Net in terms of both performance and computational
efficiency when compared with existing state-of-the-art BWE methods.
