面向语音通信与交互的麦克风阵列波束形成方法

Immersive communication and human-machine speech interface systems have to face the problem of distant sound acquisition in complex acoustic environments where noise, reverberation, echo, and competing sources may coexist. To deal with this problem, microphone arrays or more generally multichannel sound acquisition systems have to be used. The major difference between a microphone array and a multichannel system lies in how the microphone sensors are selected and organized. In the former, the microphone sensors are carefully selected to have the same or similar sensitivity, signal-to-noise ratio (SNR), and responses and they are well organized into a particular geometry. All the sensors' signals in such an array are pre-amplified with a same gain and converted to the digital domain with a same clock. In contrast, a multichannel system (either centralized or distributed) may use multiple clocks and have sensors with different characteristics. The central component of both systems are signal processing, which operates on the sensors' outputs to achieve a certain objective such as source localization, noise reduction, signal enhancement, dereverberation, source separation, to name but a few. Considering the maturity level as well as the application breadth so far, we focus in this paper on microphone arrays and present a systematic overview of the state of the art of the associated beamforming algorithms including the delay-and-sum, superdirective, differential, and adaptive beamformers. We discuss the basic principles underlying those beamformers and their pros and cons. Due to space limit, however, we will not present much detail on the derivation of every individual algorithm. The interested reader is therefore encouraged to follow the respective references listed in the paper.