research
∙
01/31/2023
Neural Target Speech Extraction: An Overview
Humans can listen to a target speaker even in challenging acoustic condi...
share
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...
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...
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 ...
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...
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...
research
∙
03/31/2022
Subjective intelligibility of speech sounds enhanced by ideal ratio mask via crowdsourced remote experiments with effective data screening
It is essential to perform speech intelligibility (SI) experiments with ...
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...
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...
research
∙
11/20/2021
Switching Independent Vector Analysis and Its Extension to Blind and Spatially Guided Convolutional Beamforming Algorithm
This paper develops a framework that can perform denoising, dereverberat...
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...
research
∙
08/04/2021
Blind and neural network-guided convolutional beamformer for joint denoising, dereverberation, and source separation
This paper proposes an approach for optimizing a Convolutional BeamForme...
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...
research
∙
07/30/2021
Speeding Up Permutation Invariant Training for Source Separation
Permutation invariant training (PIT) is a widely used training criterion...
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...
research
∙
06/07/2021
PILOT: Introducing Transformers for Probabilistic Sound Event Localization
Sound event localization aims at estimating the positions of sound sourc...
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 ...
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...
research
∙
04/17/2021
Comparison of remote experiments using crowdsourcing and laboratory experiments on speech intelligibility
Many subjective experiments have been performed to develop objective spe...
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...
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 ...
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...
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...
research
∙
02/02/2021
Multimodal Attention Fusion for Target Speaker Extraction
Target speaker extraction, which aims at extracting a target speaker's v...
research
∙
01/14/2021
Speaker activity driven neural speech extraction
Target speech extraction, which extracts the speech of a target speaker ...
research
∙
01/12/2021
Neural Network-based Virtual Microphone Estimator
Developing microphone array technologies for a small number of microphon...
research
∙
12/17/2020
Continuous Speech Separation Using Speaker Inventory for Long Multi-talker Recording
Leveraging additional speaker information to facilitate speech separatio...
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...
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, ...
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...
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...
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...
research
∙
05/20/2020
Jointly optimal denoising, dereverberation, and source separation
This paper proposes methods that can optimize a Convolutional BeamFormer...
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...
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...
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...
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...
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...
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...
research
∙
10/30/2019
Jointly optimal dereverberation and beamforming
We previously proposed an optimal (in the maximum likelihood sense) conv...
research
∙
08/06/2019
Maximum likelihood convolutional beamformer for simultaneous denoising and dereverberation
This article describes a probabilistic formulation of a Weighted Power m...
research
∙
04/03/2019
GEDI: Gammachirp Envelope Distortion Index for Predicting Intelligibility of Enhanced Speech
In this study, we proposed a new concept, gammachirp envelope distortion...
research
∙
02/21/2019
All-neural online source separation, counting, and diarization for meeting analysis
Automatic meeting analysis comprises the tasks of speaker counting, spea...
research
∙
12/20/2018
