Results 1 to 10 of about 10,574,194 (321)
Jointly optimal denoising, dereverberation, and source separation [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2020 This paper proposes methods that can optimize a Convolutional BeamFormer (CBF) for jointly performing denoising, dereverberation, and source separation (DN+DR+SS) in a computationally efficient way.
Boeddeker, Christoph +5 more
core +2 more sources
, 2011 This is the author's accepted pre-print of the article, first published as G. Evangelista, S. Marchand, M. D. Plumbley and E. Vincent. Sound source separation. In U. Zölzer (ed.), DAFX: Digital Audio Effects, 2nd edition, Chapter 14, pp. 551-588.
Evangelista, G +3 more
core +6 more sources
Music Source Separation With Band-Split RNN [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2022 The performance of music source separation (MSS) models has been greatly improved in recent years thanks to the development of novel neural network architectures and training pipelines. However, recent model designs for MSS were mainly motivated by other
Yi Luo, Jianwei Yu
semanticscholar +1 more source
Hybrid Transformers for Music Source Separation [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2022 A natural question arising in Music Source Separation (MSS) is whether long range contextual information is useful, or whether local acoustic features are sufficient. In other fields, attention based Transformers [1] have shown their ability to integrate
Simon Rouard +2 more
semanticscholar +1 more source
Music Source Separation With Band-Split Rope Transformer [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023 Music source separation (MSS) aims to separate a music recording into multiple musically distinct stems, such as vocals, bass, drums, and more. Recently, deep learning approaches such as convolutional neural networks (CNNs) and recurrent neural networks (
Wei-Tsung Lu +3 more
semanticscholar +1 more source
Moisesdb: A dataset for source separation beyond 4-stems [PDF]
International Society for Music Information Retrieval Conference, 2023 In this paper, we introduce the MoisesDB dataset for musical source separation. It consists of 240 tracks from 45 artists, covering twelve musical genres.
Igor Pereira +3 more
semanticscholar +1 more source
Universal Source Separation with Weakly Labelled Data [PDF]
arXiv.org, 2023 Universal source separation (USS) is a fundamental research task for computational auditory scene analysis, which aims to separate mono recordings into individual source tracks.
Qiuqiang Kong +6 more
semanticscholar +1 more source
Separate What You Describe: Language-Queried Audio Source Separation [PDF]
Interspeech, 2022 In this paper, we introduce the task of language-queried audio source separation (LASS), which aims to separate a target source from an audio mixture based on a natural language query of the target source (e.g.,"a man tells a joke followed by people ...
Xubo Liu +7 more
semanticscholar +1 more source
Diffusion-Based Generative Speech Source Separation [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2022 We propose DiffSep, a new single channel source separation method based on score-matching of a stochastic differential equation (SDE). We craft a tailored continuous time diffusion-mixing process starting from the separated sources and converging to a ...
Robin Scheibler +5 more
semanticscholar +1 more source
Decoupling Magnitude and Phase Estimation with Deep ResUNet for Music Source Separation [PDF]
International Society for Music Information Retrieval Conference, 2021 Deep neural network based methods have been successfully applied to music source separation. They typically learn a mapping from a mixture spectrogram to a set of source spectrograms, all with magnitudes only.
Qiuqiang Kong +4 more
semanticscholar +1 more source