SOTAVerified

Audio Source Separation

Audio Source Separation is the process of separating a mixture (e.g. a pop band recording) into isolated sounds from individual sources (e.g. just the lead vocals).

Source: Model selection for deep audio source separation via clustering analysis

Papers

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Showing 51–100 of 112 papers

TitleStatusHype
Densely Connected Multi-Dilated Convolutional Networks for Dense Prediction TasksCode0
Parallel and Flexible Sampling from Autoregressive Models via Langevin DynamicsCode1
Move2Hear: Active Audio-Visual Source Separation—0
Sampling-Frequency-Independent Audio Source Separation Using Convolution Layer Based on Impulse Invariant MethodCode0
MULTIMODAL ANALYSIS: Informed content estimation and audio source separation—0
Differentiable Model Compression via Pseudo Quantization NoiseCode1
Weakly-supervised Audio-visual Sound Source Detection and Separation—0
Compute and memory efficient universal sound source separationCode1
Music source separation conditioned on 3D point cloudsCode0
Directional Sparse Filtering using Weighted Lehmer Mean for Blind Separation of Unbalanced Speech MixturesCode1
Densely connected multidilated convolutional networks for dense prediction tasksCode0
Problems using deep generative models for probabilistic audio source separation—0
Unified Gradient Reweighting for Model Biasing with Applications to Source SeparationCode1
A Study of Transfer Learning in Music Source Separation—0
Towards Listening to 10 People Simultaneously: An Efficient Permutation Invariant Training of Audio Source Separation Using Sinkhorn's Algorithm—0
Fast accuracy estimation of deep learning based multi-class musical source separation—0
The Cone of Silence: Speech Separation by LocalizationCode1
Adversarial attacks on audio source separation—0
Structure and Automatic Segmentation of Dhrupad Vocal Bandish Audio—0
AutoClip: Adaptive Gradient Clipping for Source Separation NetworksCode1
Sudo rm -rf: Efficient Networks for Universal Audio Source SeparationCode1
OtoWorld: Towards Learning to Separate by Learning to MoveCode1
Unsupervised Audio Source Separation using Generative PriorsCode1
Time-Domain Audio Source Separation Based on Wave-U-Net Combined with Discrete Wavelet TransformCode1
Cooperative Audio Source Separation and Enhancement Using Distributed Microphone Arrays and Wearable Devices—0
J-Net: Randomly weighted U-Net for audio source separationCode0
WildMix Dataset and Spectro-Temporal Transformer Model for Monoaural Audio Source Separation—0
Improving Universal Sound Separation Using Sound Classification—0
Finding Strength in Weakness: Learning to Separate Sounds with Weak Supervision—0
Model selection for deep audio source separation via clustering analysis—0
Retrieving Signals in the Frequency Domain with Deep Complex ExtractorsCode0
Retrieving Signals with Deep Complex Extractors—0
Sams-Net: A Sliced Attention-based Neural Network for Music Source SeparationCode0
Interleaved Multitask Learning for Audio Source Separation with Independent Databases—0
Blind Audio Source Separation with Minimum-Volume Beta-Divergence NMF—0
Conditioned-U-Net: Introducing a Control Mechanism in the U-Net for Multiple Source SeparationsCode0
A Provably Correct and Robust Algorithm for Convolutive Nonnegative Matrix FactorizationCode0
Generalized Separable Nonnegative Matrix Factorization—0
Training Generative Adversarial Networks from Incomplete Observations using Factorised DiscriminatorsCode0
Co-Separating Sounds of Visual ObjectsCode0
Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets—0
Improved Speech Enhancement with the Wave-U-NetCode0
Referenceless Performance Evaluation of Audio Source Separation using Deep Neural Networks—0
Audio Source Separation Using Variational Autoencoders and Weak Class SupervisionCode0
Sparse Gaussian Process Audio Source Separation Using Spectrum Priors in the Time-DomainCode0
Improved Speech Enhancement with the Wave-U-Net—0
Generalized Multichannel Variational Autoencoder for Underdetermined Source Separation—0
Independent Deeply Learned Matrix Analysis for Multichannel Audio Source Separation—0
Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source SeparationCode1
Audio-Visual Scene Analysis with Self-Supervised Multisensory FeaturesCode0
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All datasetsAudioSetMUSIC (multi-source)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ST-SED-SEPSDR10.55—Unverified
2Co-SeparationSDR4.26—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-SeparationSAR11.3—Unverified