Jonathan Le Roux

research

∙ 08/14/2023

The Sound Demixing Challenge 2023 x2013 Cinematic Demixing Track

This paper summarizes the cinematic demixing (CDX) track of the Sound De...

0 Stefan Uhlich, et al. ∙

research

∙ 06/27/2023

Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos

To realize human-robot collaboration, robots need to execute actions for...

0 Chiori Hori, et al. ∙

research

∙ 04/04/2023

Pac-HuBERT: Self-Supervised Music Source Separation via Primitive Auditory Clustering and Hidden-Unit BERT

In spite of the progress in music source separation research, the small ...

0 Ke Chen, et al. ∙

research

∙ 03/07/2023

TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings

Since diarization and source separation of meeting data are closely rela...

0 Christoph Boeddeker, et al. ∙

research

∙ 12/14/2022

Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks

Emulating the human ability to solve the cocktail party problem, i.e., f...

0 Darius Petermann, et al. ∙

research

∙ 12/09/2022

Hyperbolic Audio Source Separation

We introduce a framework for audio source separation using embeddings on...

0 Darius Petermann, et al. ∙

research

∙ 11/22/2022

Latent Iterative Refinement for Modular Source Separation

Traditional source separation approaches train deep neural network model...

0 Dimitrios Bralios, et al. ∙

research

∙ 11/15/2022

Reverberation as Supervision for Speech Separation

This paper proposes reverberation as supervision (RAS), a novel unsuperv...

0 Rohith Aralikatti, et al. ∙

research

∙ 11/11/2022

Optimal Condition Training for Target Source Separation

Recent research has shown remarkable performance in leveraging multiple ...

0 Efthymios Tzinis, et al. ∙

research

∙ 11/04/2022

Cold Diffusion for Speech Enhancement

Diffusion models have recently shown promising results for difficult enh...

0 Hao Yen, et al. ∙

research

∙ 11/02/2022

Towards End-to-end Speaker Diarization in the Wild

Speaker diarization algorithms address the "who spoke when" problem in a...

0 Zexu Pan, et al. ∙

research

∙ 04/21/2022

STFT-Domain Neural Speech Enhancement with Very Low Algorithmic Latency

Deep learning based speech enhancement in the short-term Fourier transfo...

0 Zhong-Qiu Wang, et al. ∙

research

∙ 04/07/2022

Heterogeneous Target Speech Separation

We introduce a new paradigm for single-channel target source separation ...

1 Efthymios Tzinis, et al. ∙

research

∙ 03/08/2022

Locate This, Not That: Class-Conditioned Sound Event DOA Estimation

Existing systems for sound event localization and detection (SELD) typic...

0 Olga Slizovskaia, et al. ∙

research

∙ 03/01/2022

Extended Graph Temporal Classification for Multi-Speaker End-to-End ASR

Graph-based temporal classification (GTC), a generalized form of the con...

0 Xuankai Chang, et al. ∙

research

∙ 02/18/2022

(2.5+1)D Spatio-Temporal Scene Graphs for Video Question Answering

Spatio-temporal scene-graph approaches to video-based reasoning tasks su...

5 Anoop Cherian, et al. ∙

research

∙ 11/01/2021

Sequence Transduction with Graph-based Supervision

The recurrent neural network transducer (RNN-T) objective plays a major ...

0 Niko Moritz, et al. ∙

research

∙ 10/19/2021

The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks

The cocktail party problem aims at isolating any source of interest with...

0 Darius Petermann, et al. ∙

research

∙ 10/13/2021

Audio-Visual Scene-Aware Dialog and Reasoning using Audio-Visual Transformers with Joint Student-Teacher Learning

In previous work, we have proposed the Audio-Visual Scene-Aware Dialog (...

0 Ankit P. Shah, et al. ∙

research

∙ 10/11/2021

Advancing Momentum Pseudo-Labeling with Conformer and Initialization Strategy

Pseudo-labeling (PL), a semi-supervised learning (SSL) method where a se...

0 Yosuke Higuchi, et al. ∙

research

∙ 10/01/2021

Leveraging Low-Distortion Target Estimates for Improved Speech Enhancement

A promising approach for multi-microphone speech separation involves two...

0 Zhong-Qiu Wang, et al. ∙

research

∙ 09/24/2021

Visual Scene Graphs for Audio Source Separation

State-of-the-art approaches for visually-guided audio source separation ...

6 Moitreya Chatterjee, et al. ∙

research

∙ 08/16/2021

Convolutive Prediction for Monaural Speech Dereverberation and Noisy-Reverberant Speaker Separation

A promising approach for speech dereverberation is based on supervised l...

0 Zhong-Qiu Wang, et al. ∙

research

∙ 08/16/2021

Convolutive Prediction for Reverberant Speech Separation

We investigate the effectiveness of convolutive prediction, a novel form...

0 Zhong-Qiu Wang, et al. ∙

research

∙ 08/11/2021

On The Compensation Between Magnitude and Phase in Speech Separation

Deep neural network (DNN) based end-to-end optimization in the complex t...

0 Zhong-Qiu Wang, et al. ∙

research

∙ 08/04/2021

Optimizing Latency for Online Video CaptioningUsing Audio-Visual Transformers

Video captioning is an essential technology to understand scenes and des...

0 Chiori Hori, et al. ∙

research

∙ 07/02/2021

Dual Causal/Non-Causal Self-Attention for Streaming End-to-End Speech Recognition

Attention-based end-to-end automatic speech recognition (ASR) systems ha...

0 Niko Moritz, et al. ∙

research

∙ 06/16/2021

Momentum Pseudo-Labeling for Semi-Supervised Speech Recognition

Pseudo-labeling (PL) has been shown to be effective in semi-supervised a...

0 Yosuke Higuchi, et al. ∙

research

∙ 04/19/2021

Advanced Long-context End-to-end Speech Recognition Using Context-expanded Transformers

This paper addresses end-to-end automatic speech recognition (ASR) for l...

0 Takaaki Hori, et al. ∙

research

∙ 04/07/2021

Capturing Multi-Resolution Context by Dilated Self-Attention

Self-attention has become an important and widely used neural network co...

0 Niko Moritz, et al. ∙

research

∙ 11/26/2020

Unsupervised Domain Adaptation for Speech Recognition via Uncertainty Driven Self-Training

The performance of automatic speech recognition (ASR) systems typically ...

0 Sameer Khurana, et al. ∙

research

∙ 10/29/2020

Semi-Supervised Speech Recognition via Graph-based Temporal Classification

Semi-supervised learning has demonstrated promising results in automatic...

0 Niko Moritz, et al. ∙

research

∙ 10/22/2020

Transcription Is All You Need: Learning to Separate Musical Mixtures with Score as Supervision

Most music source separation systems require large collections of isolat...

0 Yun-Ning Hung, et al. ∙

research

∙ 09/23/2020

Multi-Pass Transformer for Machine Translation

In contrast with previous approaches where information flows only toward...

0 Peng Gao, et al. ∙

research

∙ 07/25/2020

AutoClip: Adaptive Gradient Clipping for Source Separation Networks

Clipping the gradient is a known approach to improving gradient descent,...

0 Prem Seetharaman, et al. ∙

research

∙ 07/08/2020

Spatio-Temporal Scene Graphs for Video Dialog

The Audio-Visual Scene-aware Dialog (AVSD) task requires an agent to ind...

0 Shijie Geng, et al. ∙

research

∙ 06/02/2020

Detecting Audio Attacks on ASR Systems with Dropout Uncertainty

Various adversarial audio attacks have recently been developed to fool a...

0 Tejas Jayashankar, et al. ∙

research

∙ 02/14/2020

Unsupervised Speaker Adaptation using Attention-based Speaker Memory for End-to-End ASR

We propose an unsupervised speaker adaptation method inspired by the neu...

0 Leda Sarı, et al. ∙

research

∙ 02/10/2020

End-to-End Multi-speaker Speech Recognition with Transformer

Recently, fully recurrent neural network (RNN) based end-to-end models h...

0 Xuankai Chang, et al. ∙

research

∙ 01/08/2020

Streaming automatic speech recognition with the transformer model

Encoder-decoder based sequence-to-sequence models have demonstrated stat...

0 Niko Moritz, et al. ∙

research

∙ 11/06/2019

Finding Strength in Weakness: Learning to Separate Sounds with Weak Supervision

While there has been much recent progress using deep learning techniques...

14 Fatemeh Pishdadian, et al. ∙

research

∙ 10/23/2019

Bootstrapping deep music separation from primitive auditory grouping principles

Separating an audio scene such as a cocktail party into constituent, mea...

0 Prem Seetharaman, et al. ∙

research

∙ 10/22/2019

WHAMR!: Noisy and Reverberant Single-Channel Speech Separation

While significant advances have been made in recent years in the separat...

0 Matthew Maciejewski, et al. ∙

research

∙ 10/15/2019

MIMO-SPEECH: End-to-End Multi-Channel Multi-Speaker Speech Recognition

Recently, the end-to-end approach has proven its efficacy in monaural mu...

0 Xuankai Chang, et al. ∙

research

∙ 09/18/2019

Cutting Music Source Separation Some Slakh: A Dataset to Study the Impact of Training Data Quality and Quantity

Music source separation performance has greatly improved in recent years...

0 Ethan Manilow, et al. ∙

research

∙ 07/02/2019

WHAM!: Extending Speech Separation to Noisy Environments

Recent progress in separating the speech signals from multiple overlappi...

0 Gordon Wichern, et al. ∙

research

∙ 05/08/2019

Universal Sound Separation

Recent deep learning approaches have achieved impressive performance on ...

0 Ilya Kavalerov, et al. ∙

research

∙ 11/07/2018

Class-conditional embeddings for music source separation

Isolating individual instruments in a musical mixture has a myriad of po...

0 Prem Seetharaman, et al. ∙

research

∙ 11/06/2018

SDR - half-baked or well done?

In speech enhancement and source separation, signal-to-noise ratio is a ...

0 Jonathan Le Roux, et al. ∙

research

∙ 11/06/2018

Bootstrapping single-channel source separation via unsupervised spatial clustering on stereo mixtures

Separating an audio scene into isolated sources is a fundamental problem...

0 Prem Seetharaman, et al. ∙

Jonathan Le Roux

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