---
_id: '58492'
abstract:
- lang: eng
text: A coupled finite plasticity ductile damage and failure model is proposed for
the finite element simulation of clinch joining, which incorporates stress-state
dependency and regularisation by gradient-enhancement of the damage variable.
Ductile damage is determined based on a failure indicator governed by a failure
surface in stress space. The latter is exemplary chosen as a combination of the
Hosford–Coulomb and Cockcroft–Latham–Oh failure criteria for the high and low
stress triaxiality range, respectively, to cover the wide stress range encountered
in forming. Damage is coupled to elasto-plasticity to capture the damage-induced
degradation of the stiffness and flow stress. This affects the material behaviour
up to failure, thereby realistically altering the stress state. Consequently,
especially for highly ductile materials, where substantial necking and localisation
precede material fracture, the failure prediction is enhanced. The resulting stress
softening is regularised by gradient-enhancement to obtain mesh-objective results.
The analysis of a modified punch test experiment emphasises how the damage-induced
softening effect can strongly alter the actual stress state towards failure. Moreover,
the impact of successful regularisation is shown, and the applicability of the
damage and failure model to clinch joining is proven.
article_number: '106026'
article_type: original
author:
- first_name: Johannes
full_name: Friedlein, Johannes
last_name: Friedlein
- first_name: Julia
full_name: Mergheim, Julia
last_name: Mergheim
- first_name: Paul
full_name: Steinmann, Paul
last_name: Steinmann
citation:
ama: Friedlein J, Mergheim J, Steinmann P. Modelling of stress-state-dependent ductile
damage with gradient-enhancement exemplified for clinch joining. Journal of
the Mechanics and Physics of Solids. 2025;196. doi:10.1016/j.jmps.2025.106026
apa: Friedlein, J., Mergheim, J., & Steinmann, P. (2025). Modelling of stress-state-dependent
ductile damage with gradient-enhancement exemplified for clinch joining. Journal
of the Mechanics and Physics of Solids, 196, Article 106026. https://doi.org/10.1016/j.jmps.2025.106026
bibtex: '@article{Friedlein_Mergheim_Steinmann_2025, title={Modelling of stress-state-dependent
ductile damage with gradient-enhancement exemplified for clinch joining}, volume={196},
DOI={10.1016/j.jmps.2025.106026},
number={106026}, journal={Journal of the Mechanics and Physics of Solids}, publisher={Elsevier
BV}, author={Friedlein, Johannes and Mergheim, Julia and Steinmann, Paul}, year={2025}
}'
chicago: Friedlein, Johannes, Julia Mergheim, and Paul Steinmann. “Modelling of
Stress-State-Dependent Ductile Damage with Gradient-Enhancement Exemplified for
Clinch Joining.” Journal of the Mechanics and Physics of Solids 196 (2025).
https://doi.org/10.1016/j.jmps.2025.106026.
ieee: 'J. Friedlein, J. Mergheim, and P. Steinmann, “Modelling of stress-state-dependent
ductile damage with gradient-enhancement exemplified for clinch joining,” Journal
of the Mechanics and Physics of Solids, vol. 196, Art. no. 106026, 2025, doi:
10.1016/j.jmps.2025.106026.'
mla: Friedlein, Johannes, et al. “Modelling of Stress-State-Dependent Ductile Damage
with Gradient-Enhancement Exemplified for Clinch Joining.” Journal of the Mechanics
and Physics of Solids, vol. 196, 106026, Elsevier BV, 2025, doi:10.1016/j.jmps.2025.106026.
short: J. Friedlein, J. Mergheim, P. Steinmann, Journal of the Mechanics and Physics
of Solids 196 (2025).
date_created: 2025-01-31T17:04:12Z
date_updated: 2025-01-31T17:06:22Z
doi: 10.1016/j.jmps.2025.106026
intvolume: ' 196'
keyword:
- Finite plasticity
- Ductile damage
- Gradient-enhancement
- Stress-state dependency
- Failure
language:
- iso: eng
project:
- _id: '130'
grant_number: '418701707'
name: 'TRR 285: TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '131'
name: 'TRR 285 - A: TRR 285 - Project Area A'
- _id: '139'
name: 'TRR 285 – A05: TRR 285 - Subproject A05'
publication: Journal of the Mechanics and Physics of Solids
publication_identifier:
issn:
- 0022-5096
publication_status: published
publisher: Elsevier BV
status: public
title: Modelling of stress-state-dependent ductile damage with gradient-enhancement
exemplified for clinch joining
type: journal_article
user_id: '84990'
volume: 196
year: '2025'
...
---
_id: '57472'
abstract:
- lang: eng
text: In this paper we introduce, in a Hilbert space setting, a second order dynamical
system with asymptotically vanishing damping and vanishing Tikhonov regularization
that approaches a multiobjective optimization problem with convex and differentiable
components of the objective function. Trajectory solutions are shown to exist
in finite dimensions. We prove fast convergence of the function values, quantified
in terms of a merit function. Based on the regime considered, we establish both
weak and, in some cases, strong convergence of trajectory solutions toward a weak
Pareto optimal solution. To achieve this, we apply Tikhonov regularization individually
to each component of the objective function. This work extends results from single
objective convex optimization into the multiobjective setting.
author:
- first_name: Radu Ioan
full_name: Bot, Radu Ioan
last_name: Bot
- first_name: Konstantin
full_name: Sonntag, Konstantin
id: '56399'
last_name: Sonntag
orcid: https://orcid.org/0000-0003-3384-3496
citation:
ama: Bot RI, Sonntag K. Inertial dynamics with vanishing Tikhonov regularization
for multobjective optimization. Journal of Mathematical Analysis and Applications.
Published online 2025.
apa: Bot, R. I., & Sonntag, K. (2025). Inertial dynamics with vanishing Tikhonov
regularization for multobjective optimization. Journal of Mathematical Analysis
and Applications.
bibtex: '@article{Bot_Sonntag_2025, title={Inertial dynamics with vanishing Tikhonov
regularization for multobjective optimization}, journal={Journal of Mathematical
Analysis and Applications}, author={Bot, Radu Ioan and Sonntag, Konstantin}, year={2025}
}'
chicago: Bot, Radu Ioan, and Konstantin Sonntag. “Inertial Dynamics with Vanishing
Tikhonov Regularization for Multobjective Optimization.” Journal of Mathematical
Analysis and Applications, 2025.
ieee: R. I. Bot and K. Sonntag, “Inertial dynamics with vanishing Tikhonov regularization
for multobjective optimization,” Journal of Mathematical Analysis and Applications,
2025.
mla: Bot, Radu Ioan, and Konstantin Sonntag. “Inertial Dynamics with Vanishing Tikhonov
Regularization for Multobjective Optimization.” Journal of Mathematical Analysis
and Applications, 2025.
short: R.I. Bot, K. Sonntag, Journal of Mathematical Analysis and Applications (2025).
date_created: 2024-11-28T08:58:17Z
date_updated: 2025-10-16T11:56:36Z
ddc:
- '510'
department:
- _id: '101'
- _id: '530'
- _id: '655'
external_id:
arxiv:
- '2411.18422'
file:
- access_level: open_access
content_type: application/pdf
creator: sonntagk
date_created: 2024-11-28T08:58:00Z
date_updated: 2024-11-28T08:58:00Z
file_id: '57473'
file_name: Inertial dynamics with vanishing Tikhonov regularization for multobjective
optimization.pdf
file_size: 4291134
relation: main_file
file_date_updated: 2024-11-28T08:58:00Z
has_accepted_license: '1'
keyword:
- Pareto optimization
- Lyapunov analysis
- gradient-like dynamical systems
- inertial dynamics
- asymptotic vanishing damping
- Tikhonov regularization
- strong convergence
language:
- iso: eng
main_file_link:
- url: https://arxiv.org/pdf/2411.18422
oa: '1'
publication: Journal of Mathematical Analysis and Applications
status: public
title: Inertial dynamics with vanishing Tikhonov regularization for multobjective
optimization
type: journal_article
user_id: '56399'
year: '2025'
...
---
_id: '32447'
abstract:
- lang: eng
text: 'We present a new gradient-like dynamical system related to unconstrained
convex smooth multiobjective optimization which involves inertial effects and
asymptotic vanishing damping. To the best of our knowledge, this system is the
first inertial gradient-like system for multiobjective optimization problems including
asymptotic vanishing damping, expanding the ideas previously laid out in [H. Attouch
and G. Garrigos, Multiobjective Optimization: An Inertial Dynamical Approach to
Pareto Optima, preprint, arXiv:1506.02823, 2015]. We prove existence of solutions
to this system in finite dimensions and further prove that its bounded solutions
converge weakly to weakly Pareto optimal points. In addition, we obtain a convergence
rate of order \(\mathcal{O}(t^{-2})\) for the function values measured with a
merit function. This approach presents a good basis for the development of fast
gradient methods for multiobjective optimization.'
article_type: original
author:
- first_name: Konstantin
full_name: Sonntag, Konstantin
id: '56399'
last_name: Sonntag
orcid: https://orcid.org/0000-0003-3384-3496
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: 0000-0002-3389-793X
citation:
ama: Sonntag K, Peitz S. Fast Convergence of Inertial Multiobjective Gradient-Like
Systems with Asymptotic Vanishing Damping. SIAM Journal on Optimization.
2024;34(3):2259-2286. doi:10.1137/23M1588512
apa: Sonntag, K., & Peitz, S. (2024). Fast Convergence of Inertial Multiobjective
Gradient-Like Systems with Asymptotic Vanishing Damping. SIAM Journal on Optimization,
34(3), 2259–2286. https://doi.org/10.1137/23M1588512
bibtex: '@article{Sonntag_Peitz_2024, title={Fast Convergence of Inertial Multiobjective
Gradient-Like Systems with Asymptotic Vanishing Damping}, volume={34}, DOI={10.1137/23M1588512}, number={3},
journal={SIAM Journal on Optimization}, publisher={Society for Industrial and
Applied Mathematics}, author={Sonntag, Konstantin and Peitz, Sebastian}, year={2024},
pages={2259–2286} }'
chicago: 'Sonntag, Konstantin, and Sebastian Peitz. “Fast Convergence of Inertial
Multiobjective Gradient-Like Systems with Asymptotic Vanishing Damping.” SIAM
Journal on Optimization 34, no. 3 (2024): 2259–86. https://doi.org/10.1137/23M1588512.'
ieee: 'K. Sonntag and S. Peitz, “Fast Convergence of Inertial Multiobjective Gradient-Like
Systems with Asymptotic Vanishing Damping,” SIAM Journal on Optimization,
vol. 34, no. 3, pp. 2259–2286, 2024, doi: 10.1137/23M1588512.'
mla: Sonntag, Konstantin, and Sebastian Peitz. “Fast Convergence of Inertial Multiobjective
Gradient-Like Systems with Asymptotic Vanishing Damping.” SIAM Journal on Optimization,
vol. 34, no. 3, Society for Industrial and Applied Mathematics, 2024, pp. 2259–86,
doi:10.1137/23M1588512.
short: K. Sonntag, S. Peitz, SIAM Journal on Optimization 34 (2024) 2259–2286.
date_created: 2022-07-28T11:53:02Z
date_updated: 2024-07-02T09:27:39Z
department:
- _id: '101'
- _id: '655'
doi: 10.1137/23M1588512
intvolume: ' 34'
issue: '3'
keyword:
- multiobjective optimization
- Pareto optimization
- Lyapunov analysis
- gradient-likedynamical systems
- inertial dynamics
- asymptotic vanishing damping
- fast convergence
language:
- iso: eng
page: 2259 - 2286
publication: SIAM Journal on Optimization
publication_identifier:
issn:
- 1095-7189
publication_status: published
publisher: Society for Industrial and Applied Mathematics
status: public
title: Fast Convergence of Inertial Multiobjective Gradient-Like Systems with Asymptotic
Vanishing Damping
type: journal_article
user_id: '56399'
volume: 34
year: '2024'
...
---
_id: '63988'
abstract:
- lang: eng
text: This concept summarizes recent advances in development and application of
DNP enhanced multinuclear solid-state NMR to study the molecular structure and
surface functionalization of cellulose and paper-based materials. Moreover, a
novel application is presented where DNP enhanced 13C and 15N solid-state NMR
is used to identify structure moieties formed by cross-linking of hydroxypropyl
cellulose. Given these two aspects of this concept-type of article, we thus combine
both, a review on recent findings already published and unpublished recent data
that complement the existing knowledge in the field of characterization of functional
lignocellulosic materials by DNP enhanced solid-state NMR.
author:
- first_name: Mark V.
full_name: Höfler, Mark V.
last_name: Höfler
- first_name: Jonas
full_name: Lins, Jonas
last_name: Lins
- first_name: David
full_name: Seelinger, David
last_name: Seelinger
- first_name: Lukas
full_name: Pachernegg, Lukas
last_name: Pachernegg
- first_name: Timmy
full_name: Schäfer, Timmy
last_name: Schäfer
- first_name: Stefan
full_name: Spirk, Stefan
last_name: Spirk
- first_name: Markus
full_name: Biesalski, Markus
last_name: Biesalski
- first_name: Torsten
full_name: Gutmann, Torsten
id: '118165'
last_name: Gutmann
citation:
ama: Höfler MV, Lins J, Seelinger D, et al. DNP enhanced solid-state NMR – A powerful
tool to address the surface functionalization of cellulose/paper derived materials.
Journal of Magnetic Resonance Open. 2024;21:100163. doi:10.1016/j.jmro.2024.100163
apa: Höfler, M. V., Lins, J., Seelinger, D., Pachernegg, L., Schäfer, T., Spirk,
S., Biesalski, M., & Gutmann, T. (2024). DNP enhanced solid-state NMR – A
powerful tool to address the surface functionalization of cellulose/paper derived
materials. Journal of Magnetic Resonance Open, 21, 100163. https://doi.org/10.1016/j.jmro.2024.100163
bibtex: '@article{Höfler_Lins_Seelinger_Pachernegg_Schäfer_Spirk_Biesalski_Gutmann_2024,
title={DNP enhanced solid-state NMR – A powerful tool to address the surface functionalization
of cellulose/paper derived materials}, volume={21}, DOI={10.1016/j.jmro.2024.100163},
journal={Journal of Magnetic Resonance Open}, author={Höfler, Mark V. and Lins,
Jonas and Seelinger, David and Pachernegg, Lukas and Schäfer, Timmy and Spirk,
Stefan and Biesalski, Markus and Gutmann, Torsten}, year={2024}, pages={100163}
}'
chicago: 'Höfler, Mark V., Jonas Lins, David Seelinger, Lukas Pachernegg, Timmy
Schäfer, Stefan Spirk, Markus Biesalski, and Torsten Gutmann. “DNP Enhanced Solid-State
NMR – A Powerful Tool to Address the Surface Functionalization of Cellulose/Paper
Derived Materials.” Journal of Magnetic Resonance Open 21 (2024): 100163.
https://doi.org/10.1016/j.jmro.2024.100163.'
ieee: 'M. V. Höfler et al., “DNP enhanced solid-state NMR – A powerful tool
to address the surface functionalization of cellulose/paper derived materials,”
Journal of Magnetic Resonance Open, vol. 21, p. 100163, 2024, doi: 10.1016/j.jmro.2024.100163.'
mla: Höfler, Mark V., et al. “DNP Enhanced Solid-State NMR – A Powerful Tool to
Address the Surface Functionalization of Cellulose/Paper Derived Materials.” Journal
of Magnetic Resonance Open, vol. 21, 2024, p. 100163, doi:10.1016/j.jmro.2024.100163.
short: M.V. Höfler, J. Lins, D. Seelinger, L. Pachernegg, T. Schäfer, S. Spirk,
M. Biesalski, T. Gutmann, Journal of Magnetic Resonance Open 21 (2024) 100163.
date_created: 2026-02-07T15:46:32Z
date_updated: 2026-02-17T16:16:40Z
doi: 10.1016/j.jmro.2024.100163
extern: '1'
intvolume: ' 21'
keyword:
- solid-state nmr
- dynamic nuclear polarization
- Hydroxypropyl cellulose
- Selective enhancement
- Spin labelling
language:
- iso: eng
page: '100163'
publication: Journal of Magnetic Resonance Open
status: public
title: DNP enhanced solid-state NMR – A powerful tool to address the surface functionalization
of cellulose/paper derived materials
type: journal_article
user_id: '100715'
volume: 21
year: '2024'
...
---
_id: '56097'
abstract:
- lang: eng
text: We contrast different gradient-enhancements for plasticity-damage material
models in the logarithmic strain space and compare them to reference models based
on multiplicative plasticity. The models being compared include plasticity - gradient-damage,
where the gradient-enhancement is applied on the local damage variable, and gradient-plasticity
- damage with a gradient-enhanced plastic hardening variable. Thereby, gradient-plasticity
proved to be able to simultaneously regularise plastic and ductile (plasticity-driven)
damage localisation as confirmed by numerical localisation analyses. This appears
to be especially advantageous for logarithmic strain space plasticity-damage,
because of the observed plastic localisation even for the case of plasticity with
hardening. Even though gradient-plasticity appears to be numerically more demanding,
two numerical examples indicate a good robustness and mesh objectivity in the
softening regime. Moreover, the internal length for plasticity is able to adjust
the damage zone width, similarly to gradient-damage, however ensuring a priori
that damage takes place exclusively inside the plastic zone.
article_number: '104946'
article_type: original
author:
- first_name: Johannes
full_name: Friedlein, Johannes
last_name: Friedlein
- first_name: Julia
full_name: Mergheim, Julia
last_name: Mergheim
- first_name: Paul
full_name: Steinmann, Paul
last_name: Steinmann
citation:
ama: Friedlein J, Mergheim J, Steinmann P. Efficient gradient enhancements for plasticity
with ductile damage in the logarithmic strain space. European Journal of Mechanics
- A/Solids. 2023;99. doi:10.1016/j.euromechsol.2023.104946
apa: Friedlein, J., Mergheim, J., & Steinmann, P. (2023). Efficient gradient
enhancements for plasticity with ductile damage in the logarithmic strain space.
European Journal of Mechanics - A/Solids, 99, Article 104946. https://doi.org/10.1016/j.euromechsol.2023.104946
bibtex: '@article{Friedlein_Mergheim_Steinmann_2023, title={Efficient gradient enhancements
for plasticity with ductile damage in the logarithmic strain space}, volume={99},
DOI={10.1016/j.euromechsol.2023.104946},
number={104946}, journal={European Journal of Mechanics - A/Solids}, publisher={Elsevier
BV}, author={Friedlein, Johannes and Mergheim, Julia and Steinmann, Paul}, year={2023}
}'
chicago: Friedlein, Johannes, Julia Mergheim, and Paul Steinmann. “Efficient Gradient
Enhancements for Plasticity with Ductile Damage in the Logarithmic Strain Space.”
European Journal of Mechanics - A/Solids 99 (2023). https://doi.org/10.1016/j.euromechsol.2023.104946.
ieee: 'J. Friedlein, J. Mergheim, and P. Steinmann, “Efficient gradient enhancements
for plasticity with ductile damage in the logarithmic strain space,” European
Journal of Mechanics - A/Solids, vol. 99, Art. no. 104946, 2023, doi: 10.1016/j.euromechsol.2023.104946.'
mla: Friedlein, Johannes, et al. “Efficient Gradient Enhancements for Plasticity
with Ductile Damage in the Logarithmic Strain Space.” European Journal of Mechanics
- A/Solids, vol. 99, 104946, Elsevier BV, 2023, doi:10.1016/j.euromechsol.2023.104946.
short: J. Friedlein, J. Mergheim, P. Steinmann, European Journal of Mechanics -
A/Solids 99 (2023).
date_created: 2024-09-10T15:23:49Z
date_updated: 2026-02-24T14:37:05Z
doi: 10.1016/j.euromechsol.2023.104946
intvolume: ' 99'
keyword:
- Finite plasticity
- Logarithmic strain space
- Ductile damage
- Gradient-enhancement
- Gradient-plasticity
- Gradient-damage
- Loss of ellipticity
language:
- iso: eng
project:
- _id: '130'
name: 'TRR 285: TRR 285'
- _id: '131'
name: 'TRR 285 - A: TRR 285 - Project Area A'
- _id: '139'
name: 'TRR 285 – A05: TRR 285 - Subproject A05'
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
publication: European Journal of Mechanics - A/Solids
publication_identifier:
issn:
- 0997-7538
publication_status: published
publisher: Elsevier BV
status: public
title: Efficient gradient enhancements for plasticity with ductile damage in the logarithmic
strain space
type: journal_article
user_id: '84990'
volume: 99
year: '2023'
...
---
_id: '63969'
abstract:
- lang: eng
text: A number of Ir-N-heterocyclic carbene (Ir-NHC) complexes with asymmetric N-heterocyclic
carbene (NHC) ligands have been prepared and examined for signal amplification
by reversible exchange (SABRE). Pyridine was chosen as model compound for hyperpolarization
experiments. This substrate was examined in a solvent mixture using several Ir-NHC
complexes, which differ in their NHC ligands. The SABRE polarization was created
at 6mT and the H-1 nuclear magnetic resonancesignals were detected at 7T. We show
that asymmetric NHC ligands, because of their favorable chemistry, can adapt the
SABREactive complexes to different chemical scenarios.
author:
- first_name: S.
full_name: Hadjiali, S.
last_name: Hadjiali
- first_name: R.
full_name: Savka, R.
last_name: Savka
- first_name: M.
full_name: Plaumann, M.
last_name: Plaumann
- first_name: U.
full_name: Bommerich, U.
last_name: Bommerich
- first_name: S.
full_name: Bothe, S.
last_name: Bothe
- first_name: Torsten
full_name: Gutmann, Torsten
id: '118165'
last_name: Gutmann
- first_name: T.
full_name: Ratajczyk, T.
last_name: Ratajczyk
- first_name: J.
full_name: Bernarding, J.
last_name: Bernarding
- first_name: H. H.
full_name: Limbach, H. H.
last_name: Limbach
- first_name: H.
full_name: Plenio, H.
last_name: Plenio
- first_name: G.
full_name: Buntkowsky, G.
last_name: Buntkowsky
citation:
ama: Hadjiali S, Savka R, Plaumann M, et al. Substituent Influences on the NMR Signal
Amplification of Ir Complexes with Heterocyclic Carbene Ligands. Applied Magnetic
Resonance. 2019;50(7):895–902. doi:10.1007/s00723-019-01115-x
apa: Hadjiali, S., Savka, R., Plaumann, M., Bommerich, U., Bothe, S., Gutmann, T.,
Ratajczyk, T., Bernarding, J., Limbach, H. H., Plenio, H., & Buntkowsky, G.
(2019). Substituent Influences on the NMR Signal Amplification of Ir Complexes
with Heterocyclic Carbene Ligands. Applied Magnetic Resonance, 50(7),
895–902. https://doi.org/10.1007/s00723-019-01115-x
bibtex: '@article{Hadjiali_Savka_Plaumann_Bommerich_Bothe_Gutmann_Ratajczyk_Bernarding_Limbach_Plenio_et
al._2019, title={Substituent Influences on the NMR Signal Amplification of Ir
Complexes with Heterocyclic Carbene Ligands}, volume={50}, DOI={10.1007/s00723-019-01115-x},
number={7}, journal={Applied Magnetic Resonance}, author={Hadjiali, S. and Savka,
R. and Plaumann, M. and Bommerich, U. and Bothe, S. and Gutmann, Torsten and Ratajczyk,
T. and Bernarding, J. and Limbach, H. H. and Plenio, H. and et al.}, year={2019},
pages={895–902} }'
chicago: 'Hadjiali, S., R. Savka, M. Plaumann, U. Bommerich, S. Bothe, Torsten Gutmann,
T. Ratajczyk, et al. “Substituent Influences on the NMR Signal Amplification of
Ir Complexes with Heterocyclic Carbene Ligands.” Applied Magnetic Resonance
50, no. 7 (2019): 895–902. https://doi.org/10.1007/s00723-019-01115-x.'
ieee: 'S. Hadjiali et al., “Substituent Influences on the NMR Signal Amplification
of Ir Complexes with Heterocyclic Carbene Ligands,” Applied Magnetic Resonance,
vol. 50, no. 7, pp. 895–902, 2019, doi: 10.1007/s00723-019-01115-x.'
mla: Hadjiali, S., et al. “Substituent Influences on the NMR Signal Amplification
of Ir Complexes with Heterocyclic Carbene Ligands.” Applied Magnetic Resonance,
vol. 50, no. 7, 2019, pp. 895–902, doi:10.1007/s00723-019-01115-x.
short: S. Hadjiali, R. Savka, M. Plaumann, U. Bommerich, S. Bothe, T. Gutmann, T.
Ratajczyk, J. Bernarding, H.H. Limbach, H. Plenio, G. Buntkowsky, Applied Magnetic
Resonance 50 (2019) 895–902.
date_created: 2026-02-07T15:40:18Z
date_updated: 2026-02-17T16:17:34Z
doi: 10.1007/s00723-019-01115-x
extern: '1'
intvolume: ' 50'
issue: '7'
keyword:
- dynamic nuclear-polarization
- hyperpolarization
- enhancement
- hydrogen induced polarization
- olefin-metathesis catalysts
- parahydrogen-induced polarization
- peptides
- Physics
- sabre
- spectroscopy
language:
- iso: eng
page: 895–902
publication: Applied Magnetic Resonance
publication_identifier:
issn:
- 1613-7507
status: public
title: Substituent Influences on the NMR Signal Amplification of Ir Complexes with
Heterocyclic Carbene Ligands
type: journal_article
user_id: '100715'
volume: 50
year: '2019'
...
---
_id: '11739'
abstract:
- lang: eng
text: Noise tracking is an important component of speech enhancement algorithms.
Of the many noise trackers proposed, Minimum Statistics (MS) is a particularly
popular one due to its simple parameterization and at the same time excellent
performance. In this paper we propose to further reduce the number of MS parameters
by giving an alternative derivation of an optimal smoothing constant. At the same
time the noise tracking performance is improved as is demonstrated by experiments
employing speech degraded by various noise types and at different SNR values.
author:
- first_name: Aleksej
full_name: Chinaev, Aleksej
last_name: Chinaev
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Chinaev A, Haeb-Umbach R. On Optimal Smoothing in Minimum Statistics Based
Noise Tracking. In: Interspeech 2015. ; 2015:1785-1789.'
apa: Chinaev, A., & Haeb-Umbach, R. (2015). On Optimal Smoothing in Minimum
Statistics Based Noise Tracking. In Interspeech 2015 (pp. 1785–1789).
bibtex: '@inproceedings{Chinaev_Haeb-Umbach_2015, title={On Optimal Smoothing in
Minimum Statistics Based Noise Tracking}, booktitle={Interspeech 2015}, author={Chinaev,
Aleksej and Haeb-Umbach, Reinhold}, year={2015}, pages={1785–1789} }'
chicago: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “On Optimal Smoothing in Minimum
Statistics Based Noise Tracking.” In Interspeech 2015, 1785–89, 2015.
ieee: A. Chinaev and R. Haeb-Umbach, “On Optimal Smoothing in Minimum Statistics
Based Noise Tracking,” in Interspeech 2015, 2015, pp. 1785–1789.
mla: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “On Optimal Smoothing in Minimum
Statistics Based Noise Tracking.” Interspeech 2015, 2015, pp. 1785–89.
short: 'A. Chinaev, R. Haeb-Umbach, in: Interspeech 2015, 2015, pp. 1785–1789.'
date_created: 2019-07-12T05:27:19Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
keyword:
- speech enhancement
- noise tracking
- optimal smoothing
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2015/ChHa15.pdf
oa: '1'
page: 1785-1789
publication: Interspeech 2015
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2015/ChHa15_Poster.pdf
status: public
title: On Optimal Smoothing in Minimum Statistics Based Noise Tracking
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11813'
abstract:
- lang: eng
text: 'The parametric Bayesian Feature Enhancement (BFE) and a datadriven Denoising
Autoencoder (DA) both bring performance gains in severe single-channel speech
recognition conditions. The first can be adjusted to different conditions by an
appropriate parameter setting, while the latter needs to be trained on conditions
similar to the ones expected at decoding time, making it vulnerable to a mismatch
between training and test conditions. We use a DNN backend and study reverberant
ASR under three types of mismatch conditions: different room reverberation times,
different speaker to microphone distances and the difference between artificially
reverberated data and the recordings in a reverberant environment. We show that
for these mismatch conditions BFE can provide the targets for a DA. This unsupervised
adaptation provides a performance gain over the direct use of BFE and even enables
to compensate for the mismatch of real and simulated reverberant data.'
author:
- first_name: Jahn
full_name: Heymann, Jahn
id: '9168'
last_name: Heymann
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
- first_name: P.
full_name: Golik, P.
last_name: Golik
- first_name: R.
full_name: Schlueter, R.
last_name: Schlueter
citation:
ama: 'Heymann J, Haeb-Umbach R, Golik P, Schlueter R. Unsupervised adaptation of
a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under
mismatch conditions. In: Acoustics, Speech and Signal Processing (ICASSP),
2015 IEEE International Conference On. ; 2015:5053-5057. doi:10.1109/ICASSP.2015.7178933'
apa: Heymann, J., Haeb-Umbach, R., Golik, P., & Schlueter, R. (2015). Unsupervised
adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant
asr under mismatch conditions. In Acoustics, Speech and Signal Processing (ICASSP),
2015 IEEE International Conference on (pp. 5053–5057). https://doi.org/10.1109/ICASSP.2015.7178933
bibtex: '@inproceedings{Heymann_Haeb-Umbach_Golik_Schlueter_2015, title={Unsupervised
adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant
asr under mismatch conditions}, DOI={10.1109/ICASSP.2015.7178933},
booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International
Conference on}, author={Heymann, Jahn and Haeb-Umbach, Reinhold and Golik, P.
and Schlueter, R.}, year={2015}, pages={5053–5057} }'
chicago: Heymann, Jahn, Reinhold Haeb-Umbach, P. Golik, and R. Schlueter. “Unsupervised
Adaptation of a Denoising Autoencoder by Bayesian Feature Enhancement for Reverberant
Asr under Mismatch Conditions.” In Acoustics, Speech and Signal Processing
(ICASSP), 2015 IEEE International Conference On, 5053–57, 2015. https://doi.org/10.1109/ICASSP.2015.7178933.
ieee: J. Heymann, R. Haeb-Umbach, P. Golik, and R. Schlueter, “Unsupervised adaptation
of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr
under mismatch conditions,” in Acoustics, Speech and Signal Processing (ICASSP),
2015 IEEE International Conference on, 2015, pp. 5053–5057.
mla: Heymann, Jahn, et al. “Unsupervised Adaptation of a Denoising Autoencoder by
Bayesian Feature Enhancement for Reverberant Asr under Mismatch Conditions.” Acoustics,
Speech and Signal Processing (ICASSP), 2015 IEEE International Conference On,
2015, pp. 5053–57, doi:10.1109/ICASSP.2015.7178933.
short: 'J. Heymann, R. Haeb-Umbach, P. Golik, R. Schlueter, in: Acoustics, Speech
and Signal Processing (ICASSP), 2015 IEEE International Conference On, 2015, pp.
5053–5057.'
date_created: 2019-07-12T05:28:45Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2015.7178933
keyword:
- codecs
- signal denoising
- speech recognition
- Bayesian feature enhancement
- denoising autoencoder
- reverberant ASR
- single-channel speech recognition
- speaker to microphone distances
- unsupervised adaptation
- Adaptation models
- Noise reduction
- Reverberation
- Speech
- Speech recognition
- Training
- deep neuronal networks
- denoising autoencoder
- feature enhancement
- robust speech recognition
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2015/hey_icassp_2015.pdf
oa: '1'
page: 5053-5057
publication: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International
Conference on
status: public
title: Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement
for reverberant asr under mismatch conditions
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11862'
abstract:
- lang: eng
text: In this contribution we extend a previously proposed Bayesian approach for
the enhancement of reverberant logarithmic mel power spectral coefficients for
robust automatic speech recognition to the additional compensation of background
noise. A recently proposed observation model is employed whose time-variant observation
error statistics are obtained as a side product of the inference of the a posteriori
probability density function of the clean speech feature vectors. Further a reduction
of the computational effort and the memory requirements are achieved by using
a recursive formulation of the observation model. The performance of the proposed
algorithms is first experimentally studied on a connected digits recognition task
with artificially created noisy reverberant data. It is shown that the use of
the time-variant observation error model leads to a significant error rate reduction
at low signal-to-noise ratios compared to a time-invariant model. Further experiments
were conducted on a 5000 word task recorded in a reverberant and noisy environment.
A significant word error rate reduction was obtained demonstrating the effectiveness
of the approach on real-world data.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Leutnant V, Krueger A, Haeb-Umbach R. Bayesian Feature Enhancement for Reverberation
and Noise Robust Speech Recognition. IEEE Transactions on Audio, Speech, and
Language Processing. 2013;21(8):1640-1652. doi:10.1109/TASL.2013.2258013
apa: Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2013). Bayesian Feature Enhancement
for Reverberation and Noise Robust Speech Recognition. IEEE Transactions on
Audio, Speech, and Language Processing, 21(8), 1640–1652. https://doi.org/10.1109/TASL.2013.2258013
bibtex: '@article{Leutnant_Krueger_Haeb-Umbach_2013, title={Bayesian Feature Enhancement
for Reverberation and Noise Robust Speech Recognition}, volume={21}, DOI={10.1109/TASL.2013.2258013},
number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2013},
pages={1640–1652} }'
chicago: 'Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “Bayesian
Feature Enhancement for Reverberation and Noise Robust Speech Recognition.” IEEE
Transactions on Audio, Speech, and Language Processing 21, no. 8 (2013): 1640–52.
https://doi.org/10.1109/TASL.2013.2258013.'
ieee: V. Leutnant, A. Krueger, and R. Haeb-Umbach, “Bayesian Feature Enhancement
for Reverberation and Noise Robust Speech Recognition,” IEEE Transactions on
Audio, Speech, and Language Processing, vol. 21, no. 8, pp. 1640–1652, 2013.
mla: Leutnant, Volker, et al. “Bayesian Feature Enhancement for Reverberation and
Noise Robust Speech Recognition.” IEEE Transactions on Audio, Speech, and Language
Processing, vol. 21, no. 8, 2013, pp. 1640–52, doi:10.1109/TASL.2013.2258013.
short: V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech,
and Language Processing 21 (2013) 1640–1652.
date_created: 2019-07-12T05:29:42Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2013.2258013
intvolume: ' 21'
issue: '8'
keyword:
- Bayes methods
- compensation
- error statistics
- reverberation
- speech recognition
- Bayesian feature enhancement
- background noise
- clean speech feature vectors
- compensation
- connected digits recognition task
- error statistics
- memory requirements
- noisy reverberant data
- posteriori probability density function
- recursive formulation
- reverberant logarithmic mel power spectral coefficients
- robust automatic speech recognition
- signal-to-noise ratios
- time-variant observation
- word error rate reduction
- Robust automatic speech recognition
- model-based Bayesian feature enhancement
- observation model for reverberant and noisy speech
- recursive observation model
language:
- iso: eng
page: 1640-1652
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition
type: journal_article
user_id: '44006'
volume: 21
year: '2013'
...
---
_id: '11745'
abstract:
- lang: eng
text: In this paper we present a novel noise power spectral density tracking algorithm
and its use in single-channel speech enhancement. It has the unique feature that
it is able to track the noise statistics even if speech is dominant in a given
time-frequency bin. As a consequence it can follow non-stationary noise superposed
by speech, even in the critical case of rising noise power. The algorithm requires
an initial estimate of the power spectrum of speech and is thus meant to be used
as a postprocessor to a first speech enhancement stage. An experimental comparison
with a state-of-the-art noise tracking algorithm demonstrates lower estimation
errors under low SNR conditions and smaller fluctuations of the estimated values,
resulting in improved speech quality as measured by PESQ scores.
author:
- first_name: Aleksej
full_name: Chinaev, Aleksej
last_name: Chinaev
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Dang Hai
full_name: Tran Vu, Dang Hai
last_name: Tran Vu
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Chinaev A, Krueger A, Tran Vu DH, Haeb-Umbach R. Improved Noise Power Spectral
Density Tracking by a MAP-based Postprocessor. In: 37th International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2012). ; 2012.'
apa: Chinaev, A., Krueger, A., Tran Vu, D. H., & Haeb-Umbach, R. (2012). Improved
Noise Power Spectral Density Tracking by a MAP-based Postprocessor. In 37th
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012).
bibtex: '@inproceedings{Chinaev_Krueger_Tran Vu_Haeb-Umbach_2012, title={Improved
Noise Power Spectral Density Tracking by a MAP-based Postprocessor}, booktitle={37th
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)},
author={Chinaev, Aleksej and Krueger, Alexander and Tran Vu, Dang Hai and Haeb-Umbach,
Reinhold}, year={2012} }'
chicago: Chinaev, Aleksej, Alexander Krueger, Dang Hai Tran Vu, and Reinhold Haeb-Umbach.
“Improved Noise Power Spectral Density Tracking by a MAP-Based Postprocessor.”
In 37th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2012), 2012.
ieee: A. Chinaev, A. Krueger, D. H. Tran Vu, and R. Haeb-Umbach, “Improved Noise
Power Spectral Density Tracking by a MAP-based Postprocessor,” in 37th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.
mla: Chinaev, Aleksej, et al. “Improved Noise Power Spectral Density Tracking by
a MAP-Based Postprocessor.” 37th International Conference on Acoustics, Speech
and Signal Processing (ICASSP 2012), 2012.
short: 'A. Chinaev, A. Krueger, D.H. Tran Vu, R. Haeb-Umbach, in: 37th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.'
date_created: 2019-07-12T05:27:26Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
keyword:
- MAP parameter estimation
- noise power estimation
- speech enhancement
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12.pdf
oa: '1'
publication: 37th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2012)
related_material:
link:
- description: Presentation
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12_Talk.pdf
status: public
title: Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor
type: conference
user_id: '44006'
year: '2012'
...
---
_id: '11864'
abstract:
- lang: eng
text: In this work, an observation model for the joint compensation of noise and
reverberation in the logarithmic mel power spectral density domain is considered.
It relates the features of the noisy reverberant speech to those of the non-reverberant
speech and the noise. In contrast to enhancement of features only corrupted by
reverberation (reverberant features), enhancement of noisy reverberant features
requires a more sophisticated model for the error introduced by the proposed observation
model. In a first consideration, it will be shown that this error is highly dependent
on the instantaneous ratio of the power of reverberant speech to the power of
the noise and, moreover, sensitive to the phase between reverberant speech and
noise in the short-time discrete Fourier domain. Afterwards, a statistically motivated
approach will be presented allowing for the model of the observation error to
be inferred from the error model previously used for the reverberation only case.
Finally, the developed observation error model will be utilized in a Bayesian
feature enhancement scheme, leading to improvements in word accuracy on the AURORA5
database.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Leutnant V, Krueger A, Haeb-Umbach R. A Statistical Observation Model For
Noisy Reverberant Speech Features and its Application to Robust ASR. In: Signal
Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference
On. ; 2012.'
apa: Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2012). A Statistical Observation
Model For Noisy Reverberant Speech Features and its Application to Robust ASR.
In Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International
Conference on.
bibtex: '@inproceedings{Leutnant_Krueger_Haeb-Umbach_2012, title={A Statistical
Observation Model For Noisy Reverberant Speech Features and its Application to
Robust ASR}, booktitle={Signal Processing, Communications and Computing (ICSPCC),
2012 IEEE International Conference on}, author={Leutnant, Volker and Krueger,
Alexander and Haeb-Umbach, Reinhold}, year={2012} }'
chicago: Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “A Statistical
Observation Model For Noisy Reverberant Speech Features and Its Application to
Robust ASR.” In Signal Processing, Communications and Computing (ICSPCC), 2012
IEEE International Conference On, 2012.
ieee: V. Leutnant, A. Krueger, and R. Haeb-Umbach, “A Statistical Observation Model
For Noisy Reverberant Speech Features and its Application to Robust ASR,” in Signal
Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference
on, 2012.
mla: Leutnant, Volker, et al. “A Statistical Observation Model For Noisy Reverberant
Speech Features and Its Application to Robust ASR.” Signal Processing, Communications
and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.
short: 'V. Leutnant, A. Krueger, R. Haeb-Umbach, in: Signal Processing, Communications
and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.'
date_created: 2019-07-12T05:29:44Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
keyword:
- Robust Automatic Speech Recognition
- Bayesian feature enhancement
- observation model for reverberant and noisy speech
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6335731
oa: '1'
publication: Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International
Conference on
status: public
title: A Statistical Observation Model For Noisy Reverberant Speech Features and its
Application to Robust ASR
type: conference
user_id: '44006'
year: '2012'
...
---
_id: '6081'
abstract:
- lang: eng
text: The law of prior entry states that attended objects come to consciousness
more quickly than unattended ones. This has been well established in spatial cueing
paradigms, where two task-relevant stimuli are presented near-simultaneously at
two different locations. Here, we suggest that prior entry also plays a pivotal
role in temporal attention paradigms, where stimuli appear at the same location
but at distinct moments in time, in rapid serial presentation (RSVP). Specifically,
we hypothesize that prior entry can explain temporal order reversals in reporting
two targets from RSVP. In support of this, three experiments show that cueing
attention toward either of the targets has a strong influence on order errors.
We conclude that prior entry provides a viable explanation of the way in which
relevant information is prioritized in RSVP. (PsycINFO Database Record (c) 2016
APA, all rights reserved)
author:
- first_name: Frederic
full_name: Hilkenmeier, Frederic
last_name: Hilkenmeier
- first_name: Christian N. L.
full_name: Olivers, Christian N. L.
last_name: Olivers
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
citation:
ama: 'Hilkenmeier F, Olivers CNL, Scharlau I. Prior entry and temporal attention:
Cueing affects order errors in RSVP. Journal of Experimental Psychology: Human
Perception and Performance. 2012;38(1):180-190.'
apa: 'Hilkenmeier, F., Olivers, C. N. L., & Scharlau, I. (2012). Prior entry
and temporal attention: Cueing affects order errors in RSVP. Journal of Experimental
Psychology: Human Perception and Performance, 38(1), 180–190.'
bibtex: '@article{Hilkenmeier_Olivers_Scharlau_2012, title={Prior entry and temporal
attention: Cueing affects order errors in RSVP.}, volume={38}, number={1}, journal={Journal
of Experimental Psychology: Human Perception and Performance}, author={Hilkenmeier,
Frederic and Olivers, Christian N. L. and Scharlau, Ingrid}, year={2012}, pages={180–190}
}'
chicago: 'Hilkenmeier, Frederic, Christian N. L. Olivers, and Ingrid Scharlau. “Prior
Entry and Temporal Attention: Cueing Affects Order Errors in RSVP.” Journal
of Experimental Psychology: Human Perception and Performance 38, no. 1 (2012):
180–90.'
ieee: 'F. Hilkenmeier, C. N. L. Olivers, and I. Scharlau, “Prior entry and temporal
attention: Cueing affects order errors in RSVP.,” Journal of Experimental Psychology:
Human Perception and Performance, vol. 38, no. 1, pp. 180–190, 2012.'
mla: 'Hilkenmeier, Frederic, et al. “Prior Entry and Temporal Attention: Cueing
Affects Order Errors in RSVP.” Journal of Experimental Psychology: Human Perception
and Performance, vol. 38, no. 1, 2012, pp. 180–90.'
short: 'F. Hilkenmeier, C.N.L. Olivers, I. Scharlau, Journal of Experimental Psychology:
Human Perception and Performance 38 (2012) 180–190.'
date_created: 2018-12-10T07:06:20Z
date_updated: 2022-06-06T16:35:40Z
department:
- _id: '424'
funded_apc: '1'
intvolume: ' 38'
issue: '1'
keyword:
- attentional blink
- attentional enhancement
- lag-1 sparing
- prior entry
- temporal cueing
- visual attention
- rapid serial presentation
- Adolescent
- Adult
- Attention
- Attentional Blink
- Color Perception
- Cues
- Female
- Humans
- Male
- Neuropsychological Tests
- Pattern Recognition
- Visual
- Time Factors
- Visual Perception
- Young Adult
- Cues
- Serial Recall
- Visual Attention
- Eyeblink Reflex
language:
- iso: eng
page: 180 - 190
publication: 'Journal of Experimental Psychology: Human Perception and Performance'
publication_identifier:
issn:
- 0096-1523
publication_status: published
status: public
title: 'Prior entry and temporal attention: Cueing affects order errors in RSVP.'
type: journal_article
user_id: '42165'
volume: 38
year: '2012'
...
---
_id: '11850'
abstract:
- lang: eng
text: In this paper, we present a novel blocking matrix and fixed beamformer design
for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure.
They are based on a new method for estimating the acoustical transfer function
ratios in the presence of stationary noise. The estimation method relies on solving
a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector
tracking utilizing the power iteration method is employed and shown to achieve
a high convergence speed. Simulation results demonstrate that the proposed beamformer
leads to better noise and interference reduction and reduced speech distortions
compared to other blocking matrix designs from the literature.
author:
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Krueger A, Warsitz E, Haeb-Umbach R. Speech Enhancement With a GSC-Like Structure
Employing Eigenvector-Based Transfer Function Ratios Estimation. IEEE Transactions
on Audio, Speech, and Language Processing. 2011;19(1):206-219. doi:10.1109/TASL.2010.2047324
apa: Krueger, A., Warsitz, E., & Haeb-Umbach, R. (2011). Speech Enhancement
With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios
Estimation. IEEE Transactions on Audio, Speech, and Language Processing,
19(1), 206–219. https://doi.org/10.1109/TASL.2010.2047324
bibtex: '@article{Krueger_Warsitz_Haeb-Umbach_2011, title={Speech Enhancement With
a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation},
volume={19}, DOI={10.1109/TASL.2010.2047324},
number={1}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2011},
pages={206–219} }'
chicago: 'Krueger, Alexander, Ernst Warsitz, and Reinhold Haeb-Umbach. “Speech Enhancement
With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios
Estimation.” IEEE Transactions on Audio, Speech, and Language Processing
19, no. 1 (2011): 206–19. https://doi.org/10.1109/TASL.2010.2047324.'
ieee: A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like
Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” IEEE
Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, pp.
206–219, 2011.
mla: Krueger, Alexander, et al. “Speech Enhancement With a GSC-Like Structure Employing
Eigenvector-Based Transfer Function Ratios Estimation.” IEEE Transactions on
Audio, Speech, and Language Processing, vol. 19, no. 1, 2011, pp. 206–19,
doi:10.1109/TASL.2010.2047324.
short: A. Krueger, E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech,
and Language Processing 19 (2011) 206–219.
date_created: 2019-07-12T05:29:28Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2010.2047324
intvolume: ' 19'
issue: '1'
keyword:
- acoustical transfer function ratio
- adaptive eigenvector tracking
- array signal processing
- beamformer design
- blocking matrix
- eigenvalues and eigenfunctions
- eigenvector-based transfer function ratios estimation
- generalized sidelobe canceler
- interference reduction
- iterative methods
- power iteration method
- reduced speech distortions
- reverberant enclosure
- reverberation
- speech enhancement
- stationary noise
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2011/KrWaHa11.pdf
oa: '1'
page: 206-219
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer
Function Ratios Estimation
type: journal_article
user_id: '44006'
volume: 19
year: '2011'
...
---
_id: '11846'
abstract:
- lang: eng
text: In this paper, we present a new technique for automatic speech recognition
(ASR) in reverberant environments. Our approach is aimed at the enhancement of
the logarithmic Mel power spectrum, which is computed at an intermediate stage
to obtain the widely used Mel frequency cepstral coefficients (MFCCs). Given the
reverberant logarithmic Mel power spectral coefficients (LMPSCs), a minimum mean
square error estimate of the clean LMPSCs is computed by carrying out Bayesian
inference. We employ switching linear dynamical models as an a priori model for
the dynamics of the clean LMPSCs. Further, we derive a stochastic observation
model which relates the clean to the reverberant LMPSCs through a simplified model
of the room impulse response (RIR). This model requires only two parameters, namely
RIR energy and reverberation time, which can be estimated from the captured microphone
signal. The performance of the proposed enhancement technique is studied on the
AURORA5 database and compared to that of constrained maximum-likelihood linear
regression (CMLLR). It is shown by experimental results that our approach significantly
outperforms CMLLR and that up to 80\% of the errors caused by the reverberation
are recovered. In addition to the fact that the approach is compatible with the
standard MFCC feature vectors, it leaves the ASR back-end unchanged. It is of
moderate computational complexity and suitable for real time applications.
author:
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Krueger A, Haeb-Umbach R. Model-Based Feature Enhancement for Reverberant Speech
Recognition. IEEE Transactions on Audio, Speech, and Language Processing.
2010;18(7):1692-1707. doi:10.1109/TASL.2010.2049684
apa: Krueger, A., & Haeb-Umbach, R. (2010). Model-Based Feature Enhancement
for Reverberant Speech Recognition. IEEE Transactions on Audio, Speech, and
Language Processing, 18(7), 1692–1707. https://doi.org/10.1109/TASL.2010.2049684
bibtex: '@article{Krueger_Haeb-Umbach_2010, title={Model-Based Feature Enhancement
for Reverberant Speech Recognition}, volume={18}, DOI={10.1109/TASL.2010.2049684},
number={7}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2010}, pages={1692–1707}
}'
chicago: 'Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement
for Reverberant Speech Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing 18, no. 7 (2010): 1692–1707. https://doi.org/10.1109/TASL.2010.2049684.'
ieee: A. Krueger and R. Haeb-Umbach, “Model-Based Feature Enhancement for Reverberant
Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing,
vol. 18, no. 7, pp. 1692–1707, 2010.
mla: Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement
for Reverberant Speech Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing, vol. 18, no. 7, 2010, pp. 1692–707, doi:10.1109/TASL.2010.2049684.
short: A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 18 (2010) 1692–1707.
date_created: 2019-07-12T05:29:23Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2010.2049684
intvolume: ' 18'
issue: '7'
keyword:
- ASR
- AURORA5 database
- automatic speech recognition
- Bayesian inference
- belief networks
- CMLLR
- computational complexity
- constrained maximum likelihood linear regression
- least mean squares methods
- LMPSC computation
- logarithmic Mel power spectrum
- maximum likelihood estimation
- Mel frequency cepstral coefficients
- MFCC feature vectors
- microphone signal
- minimum mean square error estimation
- model-based feature enhancement
- regression analysis
- reverberant speech recognition
- reverberation
- RIR energy
- room impulse response
- speech recognition
- stochastic observation model
- stochastic processes
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/KrHa10.pdf
oa: '1'
page: 1692-1707
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Model-Based Feature Enhancement for Reverberant Speech Recognition
type: journal_article
user_id: '44006'
volume: 18
year: '2010'
...
---
_id: '11913'
abstract:
- lang: eng
text: In this paper we propose to employ directional statistics in a complex vector
space to approach the problem of blind speech separation in the presence of spatially
correlated noise. We interpret the values of the short time Fourier transform
of the microphone signals to be draws from a mixture of complex Watson distributions,
a probabilistic model which naturally accounts for spatial aliasing. The parameters
of the density are related to the a priori source probabilities, the power of
the sources and the transfer function ratios from sources to sensors. Estimation
formulas are derived for these parameters by employing the Expectation Maximization
(EM) algorithm. The E-step corresponds to the estimation of the source presence
probabilities for each time-frequency bin, while the M-step leads to a maximum
signal-to-noise ratio (MaxSNR) beamformer in the presence of uncertainty about
the source activity. Experimental results are reported for an implementation in
a generalized sidelobe canceller (GSC) like spatial beamforming configuration
for 3 speech sources with significant coherent noise in reverberant environments,
demonstrating the usefulness of the novel modeling framework.
author:
- first_name: Dang Hai
full_name: Tran Vu, Dang Hai
last_name: Tran Vu
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Tran Vu DH, Haeb-Umbach R. Blind speech separation employing directional statistics
in an Expectation Maximization framework. In: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2010). ; 2010:241-244.
doi:10.1109/ICASSP.2010.5495994'
apa: Tran Vu, D. H., & Haeb-Umbach, R. (2010). Blind speech separation employing
directional statistics in an Expectation Maximization framework. In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010) (pp. 241–244).
https://doi.org/10.1109/ICASSP.2010.5495994
bibtex: '@inproceedings{Tran Vu_Haeb-Umbach_2010, title={Blind speech separation
employing directional statistics in an Expectation Maximization framework}, DOI={10.1109/ICASSP.2010.5495994},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2010)}, author={Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2010},
pages={241–244} }'
chicago: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
Directional Statistics in an Expectation Maximization Framework.” In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 241–44,
2010. https://doi.org/10.1109/ICASSP.2010.5495994.
ieee: D. H. Tran Vu and R. Haeb-Umbach, “Blind speech separation employing directional
statistics in an Expectation Maximization framework,” in IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010,
pp. 241–244.
mla: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
Directional Statistics in an Expectation Maximization Framework.” IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010,
pp. 241–44, doi:10.1109/ICASSP.2010.5495994.
short: 'D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.'
date_created: 2019-07-12T05:30:40Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2010.5495994
keyword:
- array signal processing
- blind source separation
- blind speech separation
- complex vector space
- complex Watson distribution
- directional statistics
- expectation-maximisation algorithm
- expectation maximization algorithm
- Fourier transform
- Fourier transforms
- generalized sidelobe canceller
- interference suppression
- maximum signal-to-noise ratio beamformer
- microphone signal
- probabilistic model
- spatial aliasing
- spatial beamforming configuration
- speech enhancement
- statistical distributions
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-2.pdf
oa: '1'
page: 241-244
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2010)
status: public
title: Blind speech separation employing directional statistics in an Expectation
Maximization framework
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '11937'
abstract:
- lang: eng
text: In automatic speech recognition, hidden Markov models (HMMs) are commonly
used for speech decoding, while switching linear dynamic models (SLDMs) can be
employed for a preceding model-based speech feature enhancement. In this paper,
these model types are combined in order to obtain a novel iterative speech feature
enhancement and recognition architecture. It is shown that speech feature enhancement
with SLDMs can be improved by feeding back information from the HMM to the enhancement
stage. Two different feedback structures are derived. In the first, the posteriors
of the HMM states are used to control the model probabilities of the SLDMs, while
in the second they are employed to directly influence the estimate of the speech
feature distribution. Both approaches lead to improvements in recognition accuracy
both on the AURORA2 and AURORA4 databases compared to non-iterative speech feature
enhancement with SLDMs. It is also shown that a combination with uncertainty decoding
further enhances performance.
author:
- first_name: Stefan
full_name: Windmann, Stefan
last_name: Windmann
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Windmann S, Haeb-Umbach R. Approaches to Iterative Speech Feature Enhancement
and Recognition. IEEE Transactions on Audio, Speech, and Language Processing.
2009;17(5):974-984. doi:10.1109/TASL.2009.2014894
apa: Windmann, S., & Haeb-Umbach, R. (2009). Approaches to Iterative Speech
Feature Enhancement and Recognition. IEEE Transactions on Audio, Speech, and
Language Processing, 17(5), 974–984. https://doi.org/10.1109/TASL.2009.2014894
bibtex: '@article{Windmann_Haeb-Umbach_2009, title={Approaches to Iterative Speech
Feature Enhancement and Recognition}, volume={17}, DOI={10.1109/TASL.2009.2014894},
number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={974–984}
}'
chicago: 'Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech
Feature Enhancement and Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing 17, no. 5 (2009): 974–84. https://doi.org/10.1109/TASL.2009.2014894.'
ieee: S. Windmann and R. Haeb-Umbach, “Approaches to Iterative Speech Feature Enhancement
and Recognition,” IEEE Transactions on Audio, Speech, and Language Processing,
vol. 17, no. 5, pp. 974–984, 2009.
mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech
Feature Enhancement and Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing, vol. 17, no. 5, 2009, pp. 974–84, doi:10.1109/TASL.2009.2014894.
short: S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 17 (2009) 974–984.
date_created: 2019-07-12T05:31:08Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/TASL.2009.2014894
intvolume: ' 17'
issue: '5'
keyword:
- AURORA2 databases
- AURORA4 databases
- automatic speech recognition
- feedback structures
- hidden Markov models
- HMM
- iterative methods
- iterative speech feature enhancement
- model probabilities
- speech decoding
- speech enhancement
- speech feature distribution
- speech recognition
- switching linear dynamic models
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-1.pdf
oa: '1'
page: 974-984
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Approaches to Iterative Speech Feature Enhancement and Recognition
type: journal_article
user_id: '44006'
volume: 17
year: '2009'
...
---
_id: '11935'
abstract:
- lang: eng
text: The generalized sidelobe canceller by Griffith and Jim is a robust beamforming
method to enhance a desired (speech) signal in the presence of stationary noise.
Its performance depends to a high degree on the construction of the blocking matrix
which produces noise reference signals for the subsequent adaptive interference
canceller. Especially in reverberated environments the beamformer may suffer from
signal leakage and reduced noise suppression. In this paper a new blocking matrix
is proposed. It is based on a generalized eigenvalue problem whose solution provides
an indirect estimation of the transfer functions from the source to the sensors.
The quality of the new generalized eigenvector blocking matrix is studied in simulated
rooms with different reverberation times and is compared to alternatives proposed
in the literature.
author:
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Warsitz E, Krueger A, Haeb-Umbach R. Speech enhancement with a new generalized
eigenvector blocking matrix for application in a generalized sidelobe canceller.
In: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008). ; 2008:73-76. doi:10.1109/ICASSP.2008.4517549'
apa: Warsitz, E., Krueger, A., & Haeb-Umbach, R. (2008). Speech enhancement
with a new generalized eigenvector blocking matrix for application in a generalized
sidelobe canceller. In IEEE International Conference on Acoustics, Speech and
Signal Processing (ICASSP 2008) (pp. 73–76). https://doi.org/10.1109/ICASSP.2008.4517549
bibtex: '@inproceedings{Warsitz_Krueger_Haeb-Umbach_2008, title={Speech enhancement
with a new generalized eigenvector blocking matrix for application in a generalized
sidelobe canceller}, DOI={10.1109/ICASSP.2008.4517549},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008)}, author={Warsitz, Ernst and Krueger, Alexander and Haeb-Umbach,
Reinhold}, year={2008}, pages={73–76} }'
chicago: Warsitz, Ernst, Alexander Krueger, and Reinhold Haeb-Umbach. “Speech Enhancement
with a New Generalized Eigenvector Blocking Matrix for Application in a Generalized
Sidelobe Canceller.” In IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP 2008), 73–76, 2008. https://doi.org/10.1109/ICASSP.2008.4517549.
ieee: E. Warsitz, A. Krueger, and R. Haeb-Umbach, “Speech enhancement with a new
generalized eigenvector blocking matrix for application in a generalized sidelobe
canceller,” in IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP 2008), 2008, pp. 73–76.
mla: Warsitz, Ernst, et al. “Speech Enhancement with a New Generalized Eigenvector
Blocking Matrix for Application in a Generalized Sidelobe Canceller.” IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008),
2008, pp. 73–76, doi:10.1109/ICASSP.2008.4517549.
short: 'E. Warsitz, A. Krueger, R. Haeb-Umbach, in: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 73–76.'
date_created: 2019-07-12T05:31:06Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2008.4517549
keyword:
- adaptive interference canceller
- adaptive signal processing
- array signal processing
- beamforming method
- eigenvalues and eigenfunctions
- generalized eigenvector blocking matrix
- generalized sidelobe canceller
- interference suppression
- matrix algebra
- noise suppression
- speech enhancement
- transfer function estimation
- transfer functions
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2008/WaKrHa08.pdf
oa: '1'
page: 73-76
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008)
status: public
title: Speech enhancement with a new generalized eigenvector blocking matrix for application
in a generalized sidelobe canceller
type: conference
user_id: '44006'
year: '2008'
...
---
_id: '11939'
abstract:
- lang: eng
text: In this paper a switching linear dynamical model (SLDM) approach for speech
feature enhancement is improved by employing more accurate models for the dynamics
of speech and noise. The model of the clean speech feature trajectory is improved
by augmenting the state vector to capture information derived from the delta features.
Further a hidden noise state variable is introduced to obtain a more elaborated
model for the noise dynamics. Approximate Bayesian inference in the SLDM is carried
out by a bank of extended Kalman filters, whose outputs are combined according
to the a posteriori probability of the individual state models. Experimental results
on the AURORA2 database show improved recognition accuracy.
author:
- first_name: Stefan
full_name: Windmann, Stefan
last_name: Windmann
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Windmann S, Haeb-Umbach R. Modeling the dynamics of speech and noise for speech
feature enhancement in ASR. In: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2008). ; 2008:4409-4412. doi:10.1109/ICASSP.2008.4518633'
apa: Windmann, S., & Haeb-Umbach, R. (2008). Modeling the dynamics of speech
and noise for speech feature enhancement in ASR. In IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2008) (pp. 4409–4412).
https://doi.org/10.1109/ICASSP.2008.4518633
bibtex: '@inproceedings{Windmann_Haeb-Umbach_2008, title={Modeling the dynamics
of speech and noise for speech feature enhancement in ASR}, DOI={10.1109/ICASSP.2008.4518633},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008)}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2008},
pages={4409–4412} }'
chicago: Windmann, Stefan, and Reinhold Haeb-Umbach. “Modeling the Dynamics of Speech
and Noise for Speech Feature Enhancement in ASR.” In IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2008), 4409–12, 2008. https://doi.org/10.1109/ICASSP.2008.4518633.
ieee: S. Windmann and R. Haeb-Umbach, “Modeling the dynamics of speech and noise
for speech feature enhancement in ASR,” in IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 4409–4412.
mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Modeling the Dynamics of Speech
and Noise for Speech Feature Enhancement in ASR.” IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 4409–12,
doi:10.1109/ICASSP.2008.4518633.
short: 'S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2008), 2008, pp. 4409–4412.'
date_created: 2019-07-12T05:31:11Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2008.4518633
keyword:
- a posteriori probability
- AURORA2 database
- Bayesian inference
- Bayes methods
- channel bank filters
- extended Kalman filter banks
- hidden noise state variable
- Kalman filters
- noise dynamics
- speech enhancement
- speech feature enhancement
- speech feature trajectory
- switching linear dynamical model approach
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2008/WiHa08-1.pdf
oa: '1'
page: 4409-4412
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008)
status: public
title: Modeling the dynamics of speech and noise for speech feature enhancement in
ASR
type: conference
user_id: '44006'
year: '2008'
...
---
_id: '11927'
abstract:
- lang: eng
text: Maximizing the output signal-to-noise ratio (SNR) of a sensor array in the
presence of spatially colored noise leads to a generalized eigenvalue problem.
While this approach has extensively been employed in narrowband (antenna) array
beamforming, it is typically not used for broadband (microphone) array beamforming
due to the uncontrolled amount of speech distortion introduced by a narrowband
SNR criterion. In this paper, we show how the distortion of the desired signal
can be controlled by a single-channel post-filter, resulting in a performance
comparable to the generalized minimum variance distortionless response beamformer,
where arbitrary transfer functions relate the source and the microphones. Results
are given both for directional and diffuse noise. A novel gradient ascent adaptation
algorithm is presented, and its good convergence properties are experimentally
revealed by comparison with alternatives from the literature. A key feature of
the proposed beamformer is that it operates blindly, i.e., it neither requires
knowledge about the array geometry nor an explicit estimation of the transfer
functions from source to sensors or the direction-of-arrival.
author:
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Warsitz E, Haeb-Umbach R. Blind Acoustic Beamforming Based on Generalized Eigenvalue
Decomposition. IEEE Transactions on Audio, Speech, and Language Processing.
2007;15(5):1529-1539. doi:10.1109/TASL.2007.898454
apa: Warsitz, E., & Haeb-Umbach, R. (2007). Blind Acoustic Beamforming Based
on Generalized Eigenvalue Decomposition. IEEE Transactions on Audio, Speech,
and Language Processing, 15(5), 1529–1539. https://doi.org/10.1109/TASL.2007.898454
bibtex: '@article{Warsitz_Haeb-Umbach_2007, title={Blind Acoustic Beamforming Based
on Generalized Eigenvalue Decomposition}, volume={15}, DOI={10.1109/TASL.2007.898454},
number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2007}, pages={1529–1539}
}'
chicago: 'Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming
Based on Generalized Eigenvalue Decomposition.” IEEE Transactions on Audio,
Speech, and Language Processing 15, no. 5 (2007): 1529–39. https://doi.org/10.1109/TASL.2007.898454.'
ieee: E. Warsitz and R. Haeb-Umbach, “Blind Acoustic Beamforming Based on Generalized
Eigenvalue Decomposition,” IEEE Transactions on Audio, Speech, and Language
Processing, vol. 15, no. 5, pp. 1529–1539, 2007.
mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming Based
on Generalized Eigenvalue Decomposition.” IEEE Transactions on Audio, Speech,
and Language Processing, vol. 15, no. 5, 2007, pp. 1529–39, doi:10.1109/TASL.2007.898454.
short: E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 15 (2007) 1529–1539.
date_created: 2019-07-12T05:30:57Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/TASL.2007.898454
intvolume: ' 15'
issue: '5'
keyword:
- acoustic signal processing
- arbitrary transfer function
- array signal processing
- blind acoustic beamforming
- direction-of-arrival
- direction-of-arrival estimation
- eigenvalues and eigenfunctions
- generalized eigenvalue decomposition
- gradient ascent adaptation algorithm
- microphone arrays
- microphones
- narrowband array beamforming
- sensor array
- single-channel post-filter
- spatially colored noise
- transfer functions
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2007/WaHa07.pdf
oa: '1'
page: 1529-1539
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition
type: journal_article
user_id: '44006'
volume: 15
year: '2007'
...
---
_id: '11943'
abstract:
- lang: eng
text: A marginalized particle filter is proposed for performing single channel speech
enhancement with a non-linear dynamic state model. The system consists of a particle
filter for tracking line spectral pair (LSP) parameters and a Kalman filter per
particle for speech enhancement. The state model for the LSPs has been learnt
on clean speech training data. In our approach parameters and speech samples are
processed at different time scales by assuming the parameters to be constant for
small blocks of data. Further enhancement is obtained by an iteration which can
be applied on these small blocks. The experiments show that similar SNR gains
are obtained as with the Kalman-LM-iterative algorithm. However better values
of the noise level and the log-spectral distance are achieved
author:
- first_name: Stefan
full_name: Windmann, Stefan
last_name: Windmann
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Windmann S, Haeb-Umbach R. Iterative Speech Enhancement using a Non-Linear
Dynamic State Model of Speech and its Parameters. In: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2006). Vol 1. ; 2006:I.
doi:10.1109/ICASSP.2006.1660058'
apa: Windmann, S., & Haeb-Umbach, R. (2006). Iterative Speech Enhancement using
a Non-Linear Dynamic State Model of Speech and its Parameters. In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) (Vol.
1, p. I). https://doi.org/10.1109/ICASSP.2006.1660058
bibtex: '@inproceedings{Windmann_Haeb-Umbach_2006, title={Iterative Speech Enhancement
using a Non-Linear Dynamic State Model of Speech and its Parameters}, volume={1},
DOI={10.1109/ICASSP.2006.1660058},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2006)}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2006},
pages={I} }'
chicago: Windmann, Stefan, and Reinhold Haeb-Umbach. “Iterative Speech Enhancement
Using a Non-Linear Dynamic State Model of Speech and Its Parameters.” In IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006),
1:I, 2006. https://doi.org/10.1109/ICASSP.2006.1660058.
ieee: S. Windmann and R. Haeb-Umbach, “Iterative Speech Enhancement using a Non-Linear
Dynamic State Model of Speech and its Parameters,” in IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2006), 2006, vol. 1, p.
I.
mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Iterative Speech Enhancement Using
a Non-Linear Dynamic State Model of Speech and Its Parameters.” IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), vol.
1, 2006, p. I, doi:10.1109/ICASSP.2006.1660058.
short: 'S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2006), 2006, p. I.'
date_created: 2019-07-12T05:31:15Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2006.1660058
intvolume: ' 1'
keyword:
- clean speech training data
- iterative methods
- iterative speech enhancement
- Kalman filter
- Kalman filters
- Kalman-LM-iterative algorithm
- line spectral pair parameters
- log-spectral distance
- marginalized particle filter
- noise level
- nonlinear dynamic state speech model
- particle filtering (numerical methods)
- single channel speech enhancement
- SNR gains
- speech enhancement
- speech samples
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2006/WiHa06-2.pdf
oa: '1'
page: I
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2006)
status: public
title: Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech
and its Parameters
type: conference
user_id: '44006'
volume: 1
year: '2006'
...