research
∙
08/08/2023
Target Speech Extraction with Conditional Diffusion Model
Diffusion model-based speech enhancement has received increased attentio...
share
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...
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...
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...
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...
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...
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...
research
∙
01/31/2023
Neural Target Speech Extraction: An Overview
Humans can listen to a target speaker even in challenging acoustic condi...
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
∙
09/09/2022
Streaming Target-Speaker ASR with Neural Transducer
Although recent advances in deep learning technology have boosted automa...
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...
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
∙
07/25/2022
ConceptBeam: Concept Driven Target Speech Extraction
We propose a novel framework for target speech extraction based on seman...
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
∙
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...
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
∙
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
∙
01/18/2022
How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR
It is challenging to improve automatic speech recognition (ASR) performa...
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
∙
11/16/2021
Attention-based Multi-hypothesis Fusion for Speech Summarization
Speech summarization, which generates a text summary from speech, can be...
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...
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
∙
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
∙
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
∙
02/14/2020
Speech Enhancement using Self-Adaptation and Multi-Head Self-Attention
This paper investigates a self-adaptation method for speech enhancement ...
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
