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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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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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12/17/2020
Continuous Speech Separation Using Speaker Inventory for Long Multi-talker Recording
Leveraging additional speaker information to facilitate speech separatio...
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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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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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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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10/02/2018
Phasebook and Friends: Leveraging Discrete Representations for Source Separation
Deep learning based speech enhancement and source separation systems hav...
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05/15/2018
A Purely End-to-end System for Multi-speaker Speech Recognition
Recently, there has been growing interest in multi-speaker speech recogn...
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04/26/2018
End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction
This paper proposes an end-to-end approach for single-channel speaker-in...
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11/21/2017
Deep Long Short-Term Memory Adaptive Beamforming Networks For Multichannel Robust Speech Recognition
Far-field speech recognition in noisy and reverberant conditions remains...
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03/14/2017
Multichannel End-to-end Speech Recognition
The field of speech recognition is in the midst of a paradigm shift: end...
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01/11/2017
Attention-Based Multimodal Fusion for Video Description
Currently successful methods for video description are based on encoder-...
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11/18/2016
Deep Clustering and Conventional Networks for Music Separation: Stronger Together
Deep clustering is the first method to handle general audio separation s...
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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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07/07/2016
Single-Channel Multi-Speaker Separation using Deep Clustering
Deep clustering is a recently introduced deep learning architecture that...
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03/23/2016
Global-Local Face Upsampling Network
Face hallucination, which is the task of generating a high-resolution fa...
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08/18/2015
Deep clustering: Discriminative embeddings for segmentation and separation
We address the problem of acoustic source separation in a deep learning ...
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09/09/2014