b'Marc Delcroix'

research

∙ 08/08/2023

Target Speech Extraction with Conditional Diffusion Model

Diffusion model-based speech enhancement has received increased attentio...

0 Naoyuki Kamo, et al. ∙

research

∙ 07/21/2023

MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems

MeetEval is an open-source toolkit to evaluate all kinds of meeting tran...

0 Thilo von Neumann, et al. ∙

research

∙ 06/14/2023

SpeechGLUE: How Well Can Self-Supervised Speech Models Capture Linguistic Knowledge?

Self-supervised learning (SSL) for speech representation has been succes...

0 Takanori Ashihara, et al. ∙

research

∙ 06/07/2023

Transfer Learning from Pre-trained Language Models Improves End-to-End Speech Summarization

End-to-end speech summarization (E2E SSum) directly summarizes input spe...

0 Kohei Matsuura, et al. ∙

research

∙ 05/24/2023

Downstream Task Agnostic Speech Enhancement with Self-Supervised Representation Loss

Self-supervised learning (SSL) is the latest breakthrough in speech proc...

0 Hiroshi Sato, et al. ∙

research

∙ 05/23/2023

Multi-Stream Extension of Variational Bayesian HMM Clustering (MS-VBx) for Combined End-to-End and Vector Clustering-based Diarization

Combining end-to-end neural speaker diarization (EEND) with vector clust...

0 Marc Delcroix, et al. ∙

research

∙ 03/02/2023

Leveraging Large Text Corpora for End-to-End Speech Summarization

End-to-end speech summarization (E2E SSum) is a technique to directly ge...

0 Kohei Matsuura, et al. ∙

research

∙ 01/31/2023

Neural Target Speech Extraction: An Overview

Humans can listen to a target speaker even in challenging acoustic condi...

0 Katerina Zmolikova, et al. ∙

research

∙ 11/29/2022

On Word Error Rate Definitions and their Efficient Computation for Multi-Speaker Speech Recognition Systems

We present a general framework to compute the word error rate (WER) of A...

0 Thilo von Neumann, et al. ∙

research

∙ 09/09/2022

Streaming Target-Speaker ASR with Neural Transducer

Although recent advances in deep learning technology have boosted automa...

0 Takafumi Moriya, et al. ∙

research

∙ 08/15/2022

Analysis of impact of emotions on target speech extraction and speech separation

Recently, the performance of blind speech separation (BSS) and target sp...

7 Jan Švec, et al. ∙

research

∙ 07/28/2022

Utterance-by-utterance overlap-aware neural diarization with Graph-PIT

Recent speaker diarization studies showed that integration of end-to-end...

0 Keisuke Kinoshita, et al. ∙

research

∙ 07/25/2022

ConceptBeam: Concept Driven Target Speech Extraction

We propose a novel framework for target speech extraction based on seman...

0 Yasunori Ohishi, et al. ∙

research

∙ 06/16/2022

Strategies to Improve Robustness of Target Speech Extraction to Enrollment Variations

Target speech extraction is a technique to extract the target speaker's ...

0 Hiroshi Sato, et al. ∙

research

∙ 05/07/2022

Mask-based Neural Beamforming for Moving Speakers with Self-Attention-based Tracking

Beamforming is a powerful tool designed to enhance speech signals from t...

0 Tsubasa Ochiai, et al. ∙

research

∙ 04/11/2022

Listen only to me! How well can target speech extraction handle false alarms?

Target speech extraction (TSE) extracts the speech of a target speaker i...

0 Marc Delcroix, et al. ∙

research

∙ 04/08/2022

SoundBeam: Target sound extraction conditioned on sound-class labels and enrollment clues for increased performance and continuous learning

In many situations, we would like to hear desired sound events (SEs) whi...

0 Marc Delcroix, et al. ∙

research

∙ 02/14/2022

Tight integration of neural- and clustering-based diarization through deep unfolding of infinite Gaussian mixture model

Speaker diarization has been investigated extensively as an important ce...

0 Keisuke Kinoshita, et al. ∙

research

∙ 01/18/2022

How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR

It is challenging to improve automatic speech recognition (ASR) performa...

0 Kazuma Iwamoto, et al. ∙

research

∙ 01/11/2022

Learning to Enhance or Not: Neural Network-Based Switching of Enhanced and Observed Signals for Overlapping Speech Recognition

The combination of a deep neural network (DNN) -based speech enhancement...

0 Hiroshi Sato, et al. ∙

research

∙ 11/16/2021

Attention-based Multi-hypothesis Fusion for Speech Summarization

Speech summarization, which generates a text summary from speech, can be...

0 Takatomo Kano, et al. ∙

research

∙ 10/31/2021

Revisiting joint decoding based multi-talker speech recognition with DNN acoustic model

In typical multi-talker speech recognition systems, a neural network-bas...

0 Martin Kocour, et al. ∙

research

∙ 10/29/2021

SA-SDR: A novel loss function for separation of meeting style data

Many state-of-the-art neural network-based source separation systems use...

0 Thilo von Neumann, et al. ∙

research

∙ 07/30/2021

Graph-PIT: Generalized permutation invariant training for continuous separation of arbitrary numbers of speakers

Automatic transcription of meetings requires handling of overlapped spee...

0 Thilo von Neumann, et al. ∙

research

∙ 07/30/2021

Speeding Up Permutation Invariant Training for Source Separation

Permutation invariant training (PIT) is a widely used training criterion...

0 Thilo von Neumann, et al. ∙

research

∙ 06/14/2021

Few-shot learning of new sound classes for target sound extraction

Target sound extraction consists of extracting the sound of a target aco...

0 Marc Delcroix, et al. ∙

research

∙ 06/07/2021

PILOT: Introducing Transformers for Probabilistic Sound Event Localization

Sound event localization aims at estimating the positions of sound sourc...

0 Christopher Schymura, et al. ∙

research

∙ 06/02/2021

Should We Always Separate?: Switching Between Enhanced and Observed Signals for Overlapping Speech Recognition

Although recent advances in deep learning technology improved automatic ...

0 Hiroshi Sato, et al. ∙

research

∙ 05/19/2021

Advances in integration of end-to-end neural and clustering-based diarization for real conversational speech

Recently, we proposed a novel speaker diarization method called End-to-E...

0 Keisuke Kinoshita, et al. ∙

research

∙ 02/28/2021

Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localization

Sound event localization frameworks based on deep neural networks have s...

0 Christopher Schymura, et al. ∙

research

∙ 02/23/2021

Dual-Path Modeling for Long Recording Speech Separation in Meetings

The continuous speech separation (CSS) is a task to separate the speech ...

0 Chenda Li, et al. ∙

research

∙ 02/23/2021

Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domain

Estimating the positions of multiple speakers can be helpful for tasks l...

0 Julio Wissing, et al. ∙

research

∙ 02/23/2021

End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend

Recently, the end-to-end approach has been successfully applied to multi...

0 Wangyou Zhang, et al. ∙

research

∙ 02/02/2021

Multimodal Attention Fusion for Target Speaker Extraction

Target speaker extraction, which aims at extracting a target speaker's v...

0 Hiroshi Sato, et al. ∙

research

∙ 01/14/2021

Speaker activity driven neural speech extraction

Target speech extraction, which extracts the speech of a target speaker ...

0 Marc Delcroix, et al. ∙

research

∙ 01/12/2021

Neural Network-based Virtual Microphone Estimator

Developing microphone array technologies for a small number of microphon...

0 Tsubasa Ochiai, et al. ∙

research

∙ 12/17/2020

Continuous Speech Separation Using Speaker Inventory for Long Multi-talker Recording

Leveraging additional speaker information to facilitate speech separatio...

0 Cong Han, et al. ∙

research

∙ 11/30/2020

Convolutive Transfer Function Invariant SDR training criteria for Multi-Channel Reverberant Speech Separation

Time-domain training criteria have proven to be very effective for the s...

0 Christoph Boeddeker, et al. ∙

research

∙ 10/26/2020

Integrating end-to-end neural and clustering-based diarization: Getting the best of both worlds

Recent diarization technologies can be categorized into two approaches, ...

0 Keisuke Kinoshita, et al. ∙

research

∙ 06/24/2020

Multi-path RNN for hierarchical modeling of long sequential data and its application to speaker stream separation

Recently, the source separation performance was greatly improved by time...

0 Keisuke Kinoshita, et al. ∙

research

∙ 06/10/2020

Listen to What You Want: Neural Network-based Universal Sound Selector

Being able to control the acoustic events (AEs) to which we want to list...

0 Tsubasa Ochiai, et al. ∙

research

∙ 06/04/2020

Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR

Most approaches to multi-talker overlapped speech separation and recogni...

0 Thilo von Neumann, et al. ∙

research

∙ 05/20/2020

Jointly optimal denoising, dereverberation, and source separation

This paper proposes methods that can optimize a Convolutional BeamFormer...

0 Tomohiro Nakatani, et al. ∙

research

∙ 05/10/2020

Cognitive-driven convolutional beamforming using EEG-based auditory attention decoding

The performance of speech enhancement algorithms in a multi-speaker scen...

0 Ali Aroudi, et al. ∙

research

∙ 03/09/2020

Improving noise robust automatic speech recognition with single-channel time-domain enhancement network

With the advent of deep learning, research on noise-robust automatic spe...

0 Keisuke Kinoshita, et al. ∙

research

∙ 03/09/2020

Tackling real noisy reverberant meetings with all-neural source separation, counting, and diarization system

Automatic meeting analysis is an essential fundamental technology requir...

0 Keisuke Kinoshita, et al. ∙

research

∙ 02/14/2020

Speech Enhancement using Self-Adaptation and Multi-Head Self-Attention

This paper investigates a self-adaptation method for speech enhancement ...

0 Yuma Koizumi, et al. ∙

research

∙ 01/23/2020

Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam

Target speech extraction, which extracts a single target source in a mix...

0 Marc Delcroix, et al. ∙

research

∙ 12/18/2019

End-to-end training of time domain audio separation and recognition

The rising interest in single-channel multi-speaker speech separation sp...

0 Thilo von Neumann, et al. ∙

research

∙ 12/18/2019

Ene-to-end training of time domain audio separation and recognition

The rising interest in single-channel multi-speaker speech separation sp...

0 Thilo von Neumann, et al. ∙

Marc Delcroix

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