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Recent interest in exploiting Deep Learning techniques for Noise Suppression,has led to the creation of Hybrid Denoising Systems that combine classic SignalProcessing with Deep Learning. In this paper, we concentrated our efforts onextending the RNNoise denoising system (arXiv:1709.08243) with the inclusion ofcomplementary features during the training phase. We present a comprehensiveexplanation of the set-up process of a modified system and present thecomparative results derived from a performance evaluation analysis, using areference version of RNNoise as control.

RNNoise-Ex: Hybrid Speech Enhancement System based on RNN and Spectral Features