Jun 9, 2020 · We introduce a robust context-aware feature extraction strategy for single-channel speech enhancement. As shown, adding recurrency results in capturing the ...

To this end, adding recurrency factor into the feature extracting CNN layers, we introduce a robust context-aware feature extraction strategy for single-.

This work introduces a robust context-aware feature extraction strategy for single-channel speech enhancement by adding recurrency factor into the feature ...

The gruCNN-SE is a feature domain enhancement model that takes noisy spectra as the input and extracts features recurrenctly over time.

arXiv 2020 · A fully recurrent feature extraction for single channel speech enhancement · Domain Generalization using Causal Matching · Few-Shot Keyword Spotting ...

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Posted: Sep 10, 2019

1: The recurrent extraction of gruCNN FC-SE model. A fully recurrent feature extraction for single channel speech enhancement. Preprint. Full-text available.

A fully recurrent feature extraction for single channel speech enhancement ... Convolutional neural network (CNN) modules are widely being used to build high-end ...

In this work, we propose a recurrent feature extraction scheme based on ConvLSTM's for single-channel SE (ConvLSTM-SE). Its performance is compared to a low ...

In this paper, we present a deep neural network architecture comprising of both convolutional neural network (CNN) and recurrent neural network (RNN) layers