In this paper we propose a deep learning-based MVDR beamforming weight estimation method. The MVDR beamforming weight can be estimated based on deep learning using GCC-PHAT without the information on the source location, while the MVDR beamforming weight requires information on the source location. As a result of an experiment with REVERB challenge data, the root mean square error between the estimated weight and the MVDR weight was found to be 0.32.
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