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Using Speech Foundational Models in Loss Functions for Hearing Aid
  Speech Enhancement

Using Speech Foundational Models in Loss Functions for Hearing Aid Speech Enhancement

18 July 2024
Robert Sutherland
George Close
Thomas Hain
Stefan Goetze
Jon Barker
ArXivPDFHTML

Papers citing "Using Speech Foundational Models in Loss Functions for Hearing Aid Speech Enhancement"

11 / 11 papers shown
Title
Speech foundation models on intelligibility prediction for
  hearing-impaired listeners
Speech foundation models on intelligibility prediction for hearing-impaired listeners
Santiago Cuervo
R. Marxer
69
7
0
24 Jan 2024
The Effect of Spoken Language on Speech Enhancement using
  Self-Supervised Speech Representation Loss Functions
The Effect of Spoken Language on Speech Enhancement using Self-Supervised Speech Representation Loss Functions
George Close
Thomas Hain
Stefan Goetze
42
8
0
27 Jul 2023
Multi-Channel Target Speaker Extraction with Refinement: The WavLab
  Submission to the Second Clarity Enhancement Challenge
Multi-Channel Target Speaker Extraction with Refinement: The WavLab Submission to the Second Clarity Enhancement Challenge
Samuele Cornell
Zhongqiu Wang
Yoshiki Masuyama
Shinji Watanabe
Manuel Pariente
Nobutaka Ono
37
12
0
15 Feb 2023
Perceive and predict: self-supervised speech representation based loss
  functions for speech enhancement
Perceive and predict: self-supervised speech representation based loss functions for speech enhancement
George Close
William Ravenscroft
Thomas Hain
Stefan Goetze
SSL
48
12
0
11 Jan 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
26
19
0
23 Jun 2022
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech
  Processing
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
Sanyuan Chen
Chengyi Wang
Zhengyang Chen
Yu-Huan Wu
Shujie Liu
...
Yao Qian
Jian Wu
Micheal Zeng
Xiangzhan Yu
Furu Wei
SSL
206
1,846
0
26 Oct 2021
HuBERT: Self-Supervised Speech Representation Learning by Masked
  Prediction of Hidden Units
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
Wei-Ning Hsu
Benjamin Bolte
Yao-Hung Hubert Tsai
Kushal Lakhotia
Ruslan Salakhutdinov
Abdel-rahman Mohamed
SSL
147
2,939
0
14 Jun 2021
Optimising Hearing Aid Fittings for Speech in Noise with a
  Differentiable Hearing Loss Model
Optimising Hearing Aid Fittings for Speech in Noise with a Differentiable Hearing Loss Model
Zehai Tu
Ning Ma
Jon Barker
40
9
0
08 Jun 2021
TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids
TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids
Igor Fedorov
Marko Stamenovic
Carl R. Jensen
Li-Chia Yang
Ari Mandell
Yiming Gan
Matthew Mattina
P. Whatmough
30
98
0
20 May 2020
SDR - half-baked or well done?
SDR - half-baked or well done?
F. Sánchez-Martínez
M. Esplà-Gomis
Hakan Erdogan
J. Hershey
138
1,191
0
06 Nov 2018
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.4K
149,842
0
22 Dec 2014
1