@inproceedings{oai:kyutech.repo.nii.ac.jp:00006304,
 author = {Mizumachi, Mitsunori and 水町, 光徳},
 book = {Proceedings of International Congress on Acoustics （ICA 2019）},
 month = {Sep},
 note = {Beamforming has been one of the important issues in the field of multi-channel signal processing including acoustic signal processing. A wide variety of beamformers have been proposed for each application. In general acoustic beamforming for antenna array and radar applications. Recently, neural network-based non-liner beamformers become popular but have a problem that causes an annoying non-liner distortion on the output signal. In the case of speech enhancement, it is serious problem because our auditory system is highly sensitive to artificial non-linear distortion on speech signals. This paper proposes to solve the problem with the relaxed dual cost functions in the neural network-based beamformer for speech enhancement. The primary cost function aims at sharpening the beam-pattern, and the second cost function is introduced to achieve decreasing speech distortion. Those cost functions are alternatively used for optimizing the beam-pattern in the frequency range of speech signals. The feasibility of the proposed method is confirmed by carrying out a listening test., 23rd International Congress on Acoustics （ICA 2019）, September 9-13, 2019, Aachen, Germany},
 publisher = {ICA 2019},
 title = {Neural Network-based Broadband Beamformer with Less Distortion},
 year = {2019},
 yomi = {ミズマチ, ミツノリ}
}