Improving music source separation based on deep neural networks through data augmentation and network blending
S Uhlich, M Porcu, F Giron, M Enenkl… - … on acoustics, speech …, 2017 - ieeexplore.ieee.org
This paper deals with the separation of music into individual instrument tracks which is
known to be a challenging problem. We describe two different deep neural network …
known to be a challenging problem. We describe two different deep neural network …
Convolutional maxout neural networks for speech separation
Speech separation based on deep neural networks (DNNs) has been widely studied
recently, and has achieved considerable success. However, previous studies are mostly …
recently, and has achieved considerable success. However, previous studies are mostly …
MDX-Mixer: Music Demixing by Leveraging Source Signals Separated by Existing Demixing Models
This paper presents MDX-Mixer, which improves music demixing (MDX) performance by
leveraging source signals separated by multiple existing MDX models. Deep-learning …
leveraging source signals separated by multiple existing MDX models. Deep-learning …
[PDF][PDF] MDX-Mixer: 複数の音楽音源分離モデルによる出力波形を時変混合するシステム
中野倫靖， 後藤真孝 - 研究報告音楽情報科学(MUS), 2022 - staff.aist.go.jp
本稿では, 音楽音響信号と, そこから複数の既存の音楽音源分離 (MDX) モデルによって分離された
音源信号とを, 時間変化する重みで混合してより高い分離性能を達成するシステム MDX-Mixer …
音源信号とを, 時間変化する重みで混合してより高い分離性能を達成するシステム MDX-Mixer …