Adaptive and Smart Beamforming in Ad-hoc Microphone Arrays by Clustering and Ranking of the Microphones

Considering the existence of a many speech degradation factors, speech enhancement has become an important topic in the field of speech processing. Beamforming is one of the well-known methods for improving the speech quality that is conventionally applied using regular (classical) microphone arrays. Due to the restrictions in the regular arrangement of microphones, in recent years there has been an emerging trend toward the microphone arrays with irregular arrangement (or so-called Ad-hoc microphone arrays). Due to the lack of knowledge about the location and the arrangement of microphones, and spreading of the microphones throughout the environment, the idea of clustering has been considered in this paper. We propose a method for the clustering of microphones in directional noise fields. For this type of noise fields, we propose a new clustering method that works based on the energy of the received signals. We have tried that the proposed clustering method to be applicable in different directional noise fields. We also propose a modified structure for the GSC beamformer by considering different roles for microphone clusters. Our evaluations indicate that in some situations, employing a microphone cluster produces superior results compared to the usage of all microphones. This, in turn, shows that the performance of the speech enhancement system can been improved using the clustering process, while the computational load is also decreased (due the reduction in the number of employed microphones).