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Acoustic beamforming has played a key role in the robust automatic speech recognition (ASR) applications. Accurate estimates of the speech and noise spatial covariance matrices (SCM) are crucial for successfully applying the minimum variance distortionless response (MVDR) beamforming. Reliable estimation of time-frequency (TF) masks can improve the estimation of the SCMs and significantly improve...
This paper presents a learning-based approach to the task of direction of arrival estimation (DOA) from microphone array input. Traditional signal processing methods such as the classic least square (LS) method rely on strong assumptions on signal models and accurate estimations of time delay of arrival (TDOA) . They only work well in relatively clean conditions, but suffer from noise and reverberation...
For nonlinear distorted images, the performance of the existing image restoration methods is limited in either visual quality or computational complexity. In this paper, we apply the recently developed technique called recurrent radial basis function network (RBFN) for nonlinear image restoration. We give the details of the construction of the recurrent RBFN network and the determination of the network...
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