Inference skipping for more efficient real-time speech enhancement with parallel RNNs
Xiaohuai Le,
Tong Lei,
Kai Chen
et al.
Abstract:Deep neural network (DNN) based speech enhancement models have attracted extensive attention due to their promising performance. However, it is difficult to deploy a powerful DNN in real-time applications because of its high computational cost. Typical compression methods such as pruning and quantization do not make good use of the data characteristics. In this paper, we introduce the Skip-RNN strategy into speech enhancement models with parallel RNNs. The states of the RNNs update intermittently without inter… Show more
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