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Attentive batch normalization for lstm-based acoustic modeling of speech recognition
[article]
2020
arXiv
pre-print
Batch normalization (BN) is an effective method to accelerate model training and improve the generalization performance of neural networks. In this paper, we propose an improved batch normalization technique called attentive batch normalization (ABN) in Long Short Term Memory (LSTM) based acoustic modeling for automatic speech recognition (ASR). In the proposed method, an auxiliary network is used to dynamically generate the scaling and shifting parameters in batch normalization, and attention
arXiv:2001.00129v1
fatcat:rco7uvhqwnapfmvazlvqda3jpa