3 accepted papers
In recent years, deep learning has surpassed traditional approaches to the problem of singing voice separation. The Wave-U-Net is a recent deep network architecture that operates directly on the time domain. The standard Wave-U- Net is trained with data augmentation and early stopping to prevent ove…
Robustness against temporal variations is important for emotion recognition from speech audio, since emotion is expressed through complex spectral patterns that can exhibit significant local dilation and compression on the time axis depending on speaker and context. To address this and potentially o…
We investigate the problem of incorporating higher-level symbolic score-like information into Automatic Music Transcription (AMT) systems to improve their performance. We use recurrent neural networks (RNNs) and their variants as music language models (MLMs) and present a generative architecture for…