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08/21/2023
TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition
We present TokenSplit, a speech separation model that acts on discrete t...
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05/18/2023
Unsupervised Multi-channel Separation and Adaptation
A key challenge in machine learning is to generalize from training data ...
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07/20/2022
AudioScopeV2: Audio-Visual Attention Architectures for Calibrated Open-Domain On-Screen Sound Separation
We introduce AudioScopeV2, a state-of-the-art universal audio-visual on-...
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07/01/2022
Distance-Based Sound Separation
We propose the novel task of distance-based sound separation, where soun...
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04/12/2022
Text-Driven Separation of Arbitrary Sounds
We propose a method of separating a desired sound source from a single-c...
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03/29/2022
CycleGAN-Based Unpaired Speech Dereverberation
Typically, neural network-based speech dereverberation models are traine...
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10/20/2021
Adapting Speech Separation to Real-World Meetings Using Mixture Invariant Training
The recently-proposed mixture invariant training (MixIT) is an unsupervi...
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06/30/2021
DF-Conformer: Integrated architecture of Conv-TasNet and Conformer using linear complexity self-attention for speech enhancement
Single-channel speech enhancement (SE) is an important task in speech pr...
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06/17/2021
Improving On-Screen Sound Separation for Open Domain Videos with Audio-Visual Self-attention
We introduce a state-of-the-art audio-visual on-screen sound separation ...
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06/01/2021
Sparse, Efficient, and Semantic Mixture Invariant Training: Taming In-the-Wild Unsupervised Sound Separation
Supervised neural network training has led to significant progress on si...
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05/05/2021
Self-Supervised Learning from Automatically Separated Sound Scenes
Real-world sound scenes consist of time-varying collections of sound sou...
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05/05/2021
End-to-End Diarization for Variable Number of Speakers with Local-Global Networks and Discriminative Speaker Embeddings
We present an end-to-end deep network model that performs meeting diariz...
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11/03/2020
Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis
Multi-speaker speech recognition of unsegmented recordings has diverse a...
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11/02/2020
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds
Recent progress in deep learning has enabled many advances in sound sepa...
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11/02/2020
What's All the FUSS About Free Universal Sound Separation Data?
We introduce the Free Universal Sound Separation (FUSS) dataset, a new c...
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11/02/2020
Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes
We propose a benchmark of state-of-the-art sound event detection systems...
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07/08/2020
Improving Sound Event Detection In Domestic Environments Using Sound Separation
Performing sound event detection on real-world recordings often implies ...
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06/23/2020
Unsupervised Sound Separation Using Mixtures of Mixtures
In recent years, rapid progress has been made on the problem of single-c...
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11/18/2019
Alternating Between Spectral and Spatial Estimation for Speech Separation and Enhancement
This work investigates alternation between spectral separation using mas...
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11/18/2019
Improving Universal Sound Separation Using Sound Classification
Deep learning approaches have recently achieved impressive performance o...
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05/08/2019
Universal Sound Separation
Recent deep learning approaches have achieved impressive performance on ...
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02/06/2019
Transfer Learning From Sound Representations For Anger Detection in Speech
In this work, we train fully convolutional networks to detect anger in s...
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11/20/2018
Differentiable Consistency Constraints for Improved Deep Speech Enhancement
In recent years, deep networks have led to dramatic improvements in spee...
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11/06/2018
SDR - half-baked or well done?
In speech enhancement and source separation, signal-to-noise ratio is a ...
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09/21/2017
Deep Recurrent NMF for Speech Separation by Unfolding Iterative Thresholding
In this paper, we propose a novel recurrent neural network architecture ...
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10/31/2016
Full-Capacity Unitary Recurrent Neural Networks
Recurrent neural networks are powerful models for processing sequential ...
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09/02/2015