OveNet: A Hyper-Range U-Net for Singing Voice Separation
Chi-Sheng Wu, Shiang Lee, Von‐Wun Soo · 2019
In the audio source separation topic, most researchers based on deep learning methods ignored higher-frequency signals due to lack of efficient data compression method. We propose a new model named OvertoneNet (OveNet) that adopts two novel concepts, frequency 1x1 convolution layers, and complex-spectrogram channels, to handle the 44.1k audio signals (Hi-Res audio signals) containing full overtones. The result shows that OveNet performs well in both objective and subjective evaluation on interference using limited training data from SiSEC2018.