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Real-time multichannel deep speech enhancement in hearing aids:
  Comparing monaural and binaural processing in complex acoustic scenarios

Real-time multichannel deep speech enhancement in hearing aids: Comparing monaural and binaural processing in complex acoustic scenarios

3 May 2024
Nils L. Westhausen
Hendrik Kayser
Theresa Jansen
Bernd T. Meyer
ArXivPDFHTML

Papers citing "Real-time multichannel deep speech enhancement in hearing aids: Comparing monaural and binaural processing in complex acoustic scenarios"

11 / 11 papers shown
Title
Binaural multichannel blind speaker separation with a causal low-latency
  and low-complexity approach
Binaural multichannel blind speaker separation with a causal low-latency and low-complexity approach
Nils L. Westhausen
Bernd T. Meyer
BDL
58
4
0
08 Dec 2023
Restoring speech intelligibility for hearing aid users with deep
  learning
Restoring speech intelligibility for hearing aid users with deep learning
P. U. Diehl
Y. Singer
Hannes Zilly
U. Schonfeld
Paul Meyer-Rachner
Mark Berry
Henning Sprekeler
Elias Sprengel
A. Pudszuhn
V. Hofmann
31
20
0
23 Jun 2022
Deep Multi-Frame MVDR Filtering for Binaural Noise Reduction
Deep Multi-Frame MVDR Filtering for Binaural Noise Reduction
Marvin Tammen
Simon Doclo
61
12
0
18 May 2022
Open community platform for hearing aid algorithm research: open Master
  Hearing Aid (openMHA)
Open community platform for hearing aid algorithm research: open Master Hearing Aid (openMHA)
H. Kayser
T. Herzke
P. Maanen
Max Zimmermann
G. Grimm
V. Hohmann
VLM
10
27
0
03 Mar 2021
Towards efficient models for real-time deep noise suppression
Towards efficient models for real-time deep noise suppression
Sebastian Braun
H. Gamper
Chandan K. A. Reddy
I. Tashev
49
108
0
22 Jan 2021
Group Communication with Context Codec for Lightweight Source Separation
Group Communication with Context Codec for Lightweight Source Separation
Yi Luo
Cong Han
N. Mesgarani
66
20
0
14 Dec 2020
AutoClip: Adaptive Gradient Clipping for Source Separation Networks
AutoClip: Adaptive Gradient Clipping for Source Separation Networks
Prem Seetharaman
Gordon Wichern
Bryan Pardo
Jonathan Le Roux
59
34
0
25 Jul 2020
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets,
  Subjective Testing Framework, and Challenge Results
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results
Chandan K. A. Reddy
Vishak Gopal
Ross Cutler
Ebrahim Beyrami
R. Cheng
...
A. Aazami
Sebastian Braun
Puneet Rana
Sriram Srinivasan
J. Gehrke
92
316
0
16 May 2020
WHAM!: Extending Speech Separation to Noisy Environments
WHAM!: Extending Speech Separation to Noisy Environments
Gordon Wichern
J. Antognini
Michael Flynn
Licheng Richard Zhu
E. McQuinn
Dwight Crow
Ethan Manilow
Jonathan Le Roux
82
345
0
02 Jul 2019
Quantization and Training of Neural Networks for Efficient
  Integer-Arithmetic-Only Inference
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
Benoit Jacob
S. Kligys
Bo Chen
Menglong Zhu
Matthew Tang
Andrew G. Howard
Hartwig Adam
Dmitry Kalenichenko
MQ
150
3,130
0
15 Dec 2017
Learning Phrase Representations using RNN Encoder-Decoder for
  Statistical Machine Translation
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho
B. V. Merrienboer
Çağlar Gülçehre
Dzmitry Bahdanau
Fethi Bougares
Holger Schwenk
Yoshua Bengio
AIMat
1.0K
23,354
0
03 Jun 2014
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