刺耳 发表于 2025-3-26 23:36:00
http://reply.papertrans.cn/17/1650/164975/164975_31.pngcharacteristic 发表于 2025-3-27 04:24:22
http://reply.papertrans.cn/17/1650/164975/164975_32.pngDEAF 发表于 2025-3-27 07:00:28
http://reply.papertrans.cn/17/1650/164975/164975_33.pngPsa617 发表于 2025-3-27 12:47:02
Deep Neural Network Based Multichannel Audio Source Separation,nally, we present its application to a speech enhancement task and a music separation task. The experimental results show the benefit of the multichannel DNN-based approach over a single-channel DNN-based approach and the multichannel nonnegative matrix factorization based iterative EM framework.foreign 发表于 2025-3-27 15:19:48
,Audio-Visual Source Separation with Alternating Diffusion Maps,ernel-based method, which is particularly designed for this task, providing an underlying representation of the common source. We demonstrate the usefulness of the obtained representation for the activity detection of the common source and discuss how it may be further used for source separation.genuine 发表于 2025-3-27 19:50:57
http://reply.papertrans.cn/17/1650/164975/164975_36.pngsemble 发表于 2025-3-28 00:30:37
http://reply.papertrans.cn/17/1650/164975/164975_37.pngBILE 发表于 2025-3-28 05:48:21
http://reply.papertrans.cn/17/1650/164975/164975_38.pngIntegrate 发表于 2025-3-28 08:13:12
Efficient Source Separation Using Bitwise Neural Networks, XNOR instead of multiplication) on binary weight matrices and quantized input signals. As a result, we show that BNNs can perform denoising with a negnigible loss of quality as compared to a corresponding network with the same structure, while reducing the network complexity significantly.Indebted 发表于 2025-3-28 12:50:36
DNN Based Mask Estimation for Supervised Speech Separation,cribe several representative supervised algorithms, mainly for monaural speech separation. For supervised separation, generalization to unseen conditions is a critical issue. The generalization capability of supervised speech separation is also discussed.