Speech signal enhancement based on deep learning in distributed acoustic sensing.

The fidelity of a speech signal deteriorates severely in a distributed acoustic sensing (DAS) system due to the influence of the random noise. In order to improve the measurement accuracy, we have theoretically and experimentally compared and analyzed the performance of the speech signal with and without a recognition and reconstruction method-based deep learning technique. A complex convolution recurrent network (CCRN) algorithm based on complex spectral mapping is constructed to enhance the information identification of speech signals.

Research Progress in Distributed Acoustic Sensing Techniques.

Distributed acoustic sensing techniques based on Rayleigh scattering have been widely used in many applications due to their unique advantages, such as long-distance detection, high spatial resolution, and wide sensing bandwidth. In this paper, we provide a review of the recent advancements in distributed acoustic sensing techniques. The research progress and operation principles are systematically reviewed.