RNNoise-Ex: Hybrid Speech Enhancement System based on RNN and Spectral Features
This work addresses noise suppression for speech processing applications, but it is incremental as it builds upon an existing hybrid system.
The paper tackled speech enhancement by extending the RNNoise system with complementary features during training, resulting in comparative performance improvements over the reference version.
Recent interest in exploiting Deep Learning techniques for Noise Suppression, has led to the creation of Hybrid Denoising Systems that combine classic Signal Processing with Deep Learning. In this paper, we concentrated our efforts on extending the RNNoise denoising system (arXiv:1709.08243) with the inclusion of complementary features during the training phase. We present a comprehensive explanation of the set-up process of a modified system and present the comparative results derived from a performance evaluation analysis, using a reference version of RNNoise as control.