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The state-of-art methods for acoustic beamforming in multi-channel ASR is based on a neural mask estimator that attempts to learn the prediction of speech and noise using a paired corpus of clean and noisy recordings (teacher model). In this paper, we att
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Unsupervised Neural Mask Estimator For Generalized Eigen-Value Beamforming Based Asr
The state-of-art methods for acoustic beamforming in multi-channel ASR is based on a neural mask estimator that attempts to learn the prediction of speech and noise using a paired corpus of clean and noisy recordings (teacher model). In this paper, we att