---
_id: '1095'
abstract:
- lang: eng
text: 'Many university students struggle with motivational problems, and gamification
has the potential to address these problems. However, using gamification currently
is rather tedious and time-consuming for instructors because current approaches
to gamification require instructors to engage in the time-consuming preparation
of course contents (e.g., for quizzes or mini-games). In reply to this issue,
we propose a “lean” approach to gamification, which relies on gamifying learning
activities rather than learning contents. The learning activities that are gamified
in the lean approach can typically be drawn from existing course syllabi (e.g.,
attend certain lectures, hand in assignments, read book chapters and articles).
Hence, compared to existing approaches, lean gamification substantially lowers
the time requirements posed on instructors for gamifying a given course. Drawing
on research on limited attention and the present bias, we provide the theoretical
foundation for the lean gamification approach. In addition, we present a mobile
application that implements lean gamification and outline a mixed-methods study
that is currently under way for evaluating whether lean gamification does indeed
have the potential to increase students’ motivation. We thereby hope to allow
more students and instructors to benefit from the advantages of gamification. '
author:
- first_name: Thomas
full_name: John, Thomas
id: '3952'
last_name: John
- first_name: Matthias
full_name: Feldotto, Matthias
id: '14052'
last_name: Feldotto
orcid: 0000-0003-1348-6516
- first_name: Paul
full_name: Hemsen, Paul
id: '22546'
last_name: Hemsen
- first_name: Katrin
full_name: Klingsieck, Katrin
last_name: Klingsieck
- first_name: Dennis
full_name: Kundisch, Dennis
id: '21117'
last_name: Kundisch
- first_name: Mike
full_name: Langendorf, Mike
last_name: Langendorf
citation:
ama: 'John T, Feldotto M, Hemsen P, Klingsieck K, Kundisch D, Langendorf M. Towards
a Lean Approach for Gamifying Education. In: Proceedings of the 25th European
Conference on Information Systems (ECIS). ; 2017:2970-2979.'
apa: John, T., Feldotto, M., Hemsen, P., Klingsieck, K., Kundisch, D., & Langendorf,
M. (2017). Towards a Lean Approach for Gamifying Education. In Proceedings
of the 25th European Conference on Information Systems (ECIS) (pp. 2970–2979).
bibtex: '@inproceedings{John_Feldotto_Hemsen_Klingsieck_Kundisch_Langendorf_2017,
title={Towards a Lean Approach for Gamifying Education}, booktitle={Proceedings
of the 25th European Conference on Information Systems (ECIS)}, author={John,
Thomas and Feldotto, Matthias and Hemsen, Paul and Klingsieck, Katrin and Kundisch,
Dennis and Langendorf, Mike}, year={2017}, pages={2970–2979} }'
chicago: John, Thomas, Matthias Feldotto, Paul Hemsen, Katrin Klingsieck, Dennis
Kundisch, and Mike Langendorf. “Towards a Lean Approach for Gamifying Education.”
In Proceedings of the 25th European Conference on Information Systems (ECIS),
2970–79, 2017.
ieee: T. John, M. Feldotto, P. Hemsen, K. Klingsieck, D. Kundisch, and M. Langendorf,
“Towards a Lean Approach for Gamifying Education,” in Proceedings of the 25th
European Conference on Information Systems (ECIS), 2017, pp. 2970–2979.
mla: John, Thomas, et al. “Towards a Lean Approach for Gamifying Education.” Proceedings
of the 25th European Conference on Information Systems (ECIS), 2017, pp. 2970–79.
short: 'T. John, M. Feldotto, P. Hemsen, K. Klingsieck, D. Kundisch, M. Langendorf,
in: Proceedings of the 25th European Conference on Information Systems (ECIS),
2017, pp. 2970–2979.'
date_created: 2018-01-05T08:39:41Z
date_updated: 2022-01-06T06:50:53Z
ddc:
- '000'
department:
- _id: '63'
- _id: '541'
- _id: '178'
- _id: '185'
file:
- access_level: closed
content_type: application/pdf
creator: feldi
date_created: 2018-10-31T17:02:07Z
date_updated: 2018-10-31T17:02:07Z
file_id: '5232'
file_name: TOWARDS A LEAN APPROACH TO GAMIFYING EDUCATION.pdf
file_size: 485333
relation: main_file
success: 1
file_date_updated: 2018-10-31T17:02:07Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://aisel.aisnet.org/ecis2017_rip/46
oa: '1'
page: 2970-2979
publication: Proceedings of the 25th European Conference on Information Systems (ECIS)
status: public
title: Towards a Lean Approach for Gamifying Education
type: conference
user_id: '14052'
year: '2017'
...
---
_id: '110'
abstract:
- lang: eng
text: 'We consider an extension of the dynamic speed scaling scheduling model introduced
by Yao et al.: A set of jobs, each with a release time, deadline, and workload,
has to be scheduled on a single, speed-scalable processor. Both the maximum allowed
speed of the processor and the energy costs may vary continuously over time. The
objective is to find a feasible schedule that minimizes the total energy costs.
Theoretical algorithm design for speed scaling problems often tends to discretize
problems, as our tools in the discrete realm are often better developed or understood.
Using the above speed scaling variant with variable, continuous maximal processor
speeds and energy prices as an example, we demonstrate that a more direct approach
via tools from variational calculus can not only lead to a very concise and elegant
formulation and analysis, but also avoids the “explosion of variables/constraints”
that often comes with discretizing. Using well-known tools from calculus of variations,
we derive combinatorial optimality characteristics for our continuous problem
and provide a quite concise and simple correctness proof.'
author:
- first_name: Antonios
full_name: Antoniadis, Antonios
last_name: Antoniadis
- first_name: Peter
full_name: Kling, Peter
last_name: Kling
- first_name: Sebastian
full_name: Ott, Sebastian
last_name: Ott
- first_name: Sören
full_name: Riechers, Sören
last_name: Riechers
citation:
ama: 'Antoniadis A, Kling P, Ott S, Riechers S. Continuous Speed Scaling with Variability:
A Simple and Direct Approach. Theoretical Computer Science. 2017:1-13.
doi:10.1016/j.tcs.2017.03.021'
apa: 'Antoniadis, A., Kling, P., Ott, S., & Riechers, S. (2017). Continuous
Speed Scaling with Variability: A Simple and Direct Approach. Theoretical Computer
Science, 1–13. https://doi.org/10.1016/j.tcs.2017.03.021'
bibtex: '@article{Antoniadis_Kling_Ott_Riechers_2017, title={Continuous Speed Scaling
with Variability: A Simple and Direct Approach}, DOI={10.1016/j.tcs.2017.03.021},
journal={Theoretical Computer Science}, publisher={Elsevier}, author={Antoniadis,
Antonios and Kling, Peter and Ott, Sebastian and Riechers, Sören}, year={2017},
pages={1–13} }'
chicago: 'Antoniadis, Antonios, Peter Kling, Sebastian Ott, and Sören Riechers.
“Continuous Speed Scaling with Variability: A Simple and Direct Approach.” Theoretical
Computer Science, 2017, 1–13. https://doi.org/10.1016/j.tcs.2017.03.021.'
ieee: 'A. Antoniadis, P. Kling, S. Ott, and S. Riechers, “Continuous Speed Scaling
with Variability: A Simple and Direct Approach,” Theoretical Computer Science,
pp. 1–13, 2017.'
mla: 'Antoniadis, Antonios, et al. “Continuous Speed Scaling with Variability: A
Simple and Direct Approach.” Theoretical Computer Science, Elsevier, 2017,
pp. 1–13, doi:10.1016/j.tcs.2017.03.021.'
short: A. Antoniadis, P. Kling, S. Ott, S. Riechers, Theoretical Computer Science
(2017) 1–13.
date_created: 2017-10-17T12:41:13Z
date_updated: 2022-01-06T06:50:55Z
ddc:
- '040'
department:
- _id: '63'
doi: 10.1016/j.tcs.2017.03.021
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T13:07:43Z
date_updated: 2018-03-21T13:07:43Z
file_id: '1567'
file_name: 110-TCSSubmission.pdf
file_size: 494600
relation: main_file
success: 1
file_date_updated: 2018-03-21T13:07:43Z
has_accepted_license: '1'
language:
- iso: eng
page: 1-13
project:
- _id: '1'
name: SFB 901
- _id: '16'
name: SFB 901 - Subprojekt C4
- _id: '4'
name: SFB 901 - Project Area C
publication: Theoretical Computer Science
publisher: Elsevier
status: public
title: 'Continuous Speed Scaling with Variability: A Simple and Direct Approach'
type: journal_article
user_id: '477'
year: '2017'
...
---
_id: '117'
author:
- first_name: Pascal
full_name: Bemmann, Pascal
id: '32571'
last_name: Bemmann
citation:
ama: Bemmann P. Attribute-Based Signatures Using Structure Preserving Signatures.
Universität Paderborn; 2017.
apa: Bemmann, P. (2017). Attribute-based Signatures using Structure Preserving
Signatures. Universität Paderborn.
bibtex: '@book{Bemmann_2017, title={Attribute-based Signatures using Structure Preserving
Signatures}, publisher={Universität Paderborn}, author={Bemmann, Pascal}, year={2017}
}'
chicago: Bemmann, Pascal. Attribute-Based Signatures Using Structure Preserving
Signatures. Universität Paderborn, 2017.
ieee: P. Bemmann, Attribute-based Signatures using Structure Preserving Signatures.
Universität Paderborn, 2017.
mla: Bemmann, Pascal. Attribute-Based Signatures Using Structure Preserving Signatures.
Universität Paderborn, 2017.
short: P. Bemmann, Attribute-Based Signatures Using Structure Preserving Signatures,
Universität Paderborn, 2017.
date_created: 2017-10-17T12:41:14Z
date_updated: 2022-01-06T06:51:06Z
department:
- _id: '64'
project:
- _id: '1'
name: SFB 901
- _id: '13'
name: SFB 901 - Subprojekt C1
- _id: '4'
name: SFB 901 - Project Area C
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
title: Attribute-based Signatures using Structure Preserving Signatures
type: mastersthesis
user_id: '25078'
year: '2017'
...
---
_id: '11717'
abstract:
- lang: eng
text: In this work, we address the limited availability of large annotated databases
for real-life audio event detection by utilizing the concept of transfer learning.
This technique aims to transfer knowledge from a source domain to a target domain,
even if source and target have different feature distributions and label sets.
We hypothesize that all acoustic events share the same inventory of basic acoustic
building blocks and differ only in the temporal order of these acoustic units.
We then construct a deep neural network with convolutional layers for extracting
the acoustic units and a recurrent layer for capturing the temporal order. Under
the above hypothesis, transfer learning from a source to a target domain with
a different acoustic event inventory is realized by transferring the convolutional
layers from the source to the target domain. The recurrent layer is, however,
learnt directly from the target domain. Experiments on the transfer from a synthetic
source database to the reallife target database of DCASE 2016 demonstrate that
transfer learning leads to improved detection performance on average. However,
the successful transfer to detect events which are very different from what was
seen in the source domain, could not be verified.
author:
- first_name: Prerna
full_name: Arora, Prerna
last_name: Arora
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Arora P, Haeb-Umbach R. A Study on Transfer Learning for Acoustic Event Detection
in a Real Life Scenario. In: IEEE 19th International Workshop on Multimedia
Signal Processing (MMSP). ; 2017.'
apa: Arora, P., & Haeb-Umbach, R. (2017). A Study on Transfer Learning for Acoustic
Event Detection in a Real Life Scenario. In IEEE 19th International Workshop
on Multimedia Signal Processing (MMSP).
bibtex: '@inproceedings{Arora_Haeb-Umbach_2017, title={A Study on Transfer Learning
for Acoustic Event Detection in a Real Life Scenario}, booktitle={IEEE 19th International
Workshop on Multimedia Signal Processing (MMSP)}, author={Arora, Prerna and Haeb-Umbach,
Reinhold}, year={2017} }'
chicago: Arora, Prerna, and Reinhold Haeb-Umbach. “A Study on Transfer Learning
for Acoustic Event Detection in a Real Life Scenario.” In IEEE 19th International
Workshop on Multimedia Signal Processing (MMSP), 2017.
ieee: P. Arora and R. Haeb-Umbach, “A Study on Transfer Learning for Acoustic Event
Detection in a Real Life Scenario,” in IEEE 19th International Workshop on
Multimedia Signal Processing (MMSP), 2017.
mla: Arora, Prerna, and Reinhold Haeb-Umbach. “A Study on Transfer Learning for
Acoustic Event Detection in a Real Life Scenario.” IEEE 19th International
Workshop on Multimedia Signal Processing (MMSP), 2017.
short: 'P. Arora, R. Haeb-Umbach, in: IEEE 19th International Workshop on Multimedia
Signal Processing (MMSP), 2017.'
date_created: 2019-07-12T05:26:54Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/MMSP_2017_AroraHaeb.pdf
oa: '1'
publication: IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2017/MMSP_2017_AroraHaeb_poster.pdf
status: public
title: A Study on Transfer Learning for Acoustic Event Detection in a Real Life Scenario
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11735'
abstract:
- lang: eng
text: This report describes the computation of gradients by algorithmic differentiation
for statistically optimum beamforming operations. Especially the derivation of
complex-valued functions is a key component of this approach. Therefore the real-valued
algorithmic differentiation is extended via the complex-valued chain rule. In
addition to the basic mathematic operations the derivative of the eigenvalue problem
with complex-valued eigenvectors is one of the key results of this report. The
potential of this approach is shown with experimental results on the CHiME-3 challenge
database. There, the beamforming task is used as a front-end for an ASR system.
With the developed derivatives a joint optimization of a speech enhancement and
speech recognition system w.r.t. the recognition optimization criterion is possible.
author:
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Patrick
full_name: Hanebrink, Patrick
last_name: Hanebrink
- first_name: Lukas
full_name: Drude, Lukas
id: '11213'
last_name: Drude
- 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
citation:
ama: Boeddeker C, Hanebrink P, Drude L, Heymann J, Haeb-Umbach R. On the Computation
of Complex-Valued Gradients with Application to Statistically Optimum Beamforming.;
2017.
apa: Boeddeker, C., Hanebrink, P., Drude, L., Heymann, J., & Haeb-Umbach, R.
(2017). On the Computation of Complex-valued Gradients with Application to
Statistically Optimum Beamforming.
bibtex: '@book{Boeddeker_Hanebrink_Drude_Heymann_Haeb-Umbach_2017, title={On the
Computation of Complex-valued Gradients with Application to Statistically Optimum
Beamforming}, author={Boeddeker, Christoph and Hanebrink, Patrick and Drude, Lukas
and Heymann, Jahn and Haeb-Umbach, Reinhold}, year={2017} }'
chicago: Boeddeker, Christoph, Patrick Hanebrink, Lukas Drude, Jahn Heymann, and
Reinhold Haeb-Umbach. On the Computation of Complex-Valued Gradients with Application
to Statistically Optimum Beamforming, 2017.
ieee: C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, and R. Haeb-Umbach, On
the Computation of Complex-valued Gradients with Application to Statistically
Optimum Beamforming. 2017.
mla: Boeddeker, Christoph, et al. On the Computation of Complex-Valued Gradients
with Application to Statistically Optimum Beamforming. 2017.
short: C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, R. Haeb-Umbach, On the
Computation of Complex-Valued Gradients with Application to Statistically Optimum
Beamforming, 2017.
date_created: 2019-07-12T05:27:15Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/ArXiv_2017_BoeddekerHanebrinkHaeb_Article.pdf
oa: '1'
status: public
title: On the Computation of Complex-valued Gradients with Application to Statistically
Optimum Beamforming
type: report
user_id: '40767'
year: '2017'
...
---
_id: '11736'
abstract:
- lang: eng
text: In this paper we show how a neural network for spectral mask estimation for
an acoustic beamformer can be optimized by algorithmic differentiation. Using
the beamformer output SNR as the objective function to maximize, the gradient
is propagated through the beamformer all the way to the neural network which provides
the clean speech and noise masks from which the beamformer coefficients are estimated
by eigenvalue decomposition. A key theoretical result is the derivative of an
eigenvalue problem involving complex-valued eigenvectors. Experimental results
on the CHiME-3 challenge database demonstrate the effectiveness of the approach.
The tools developed in this paper are a key component for an end-to-end optimization
of speech enhancement and speech recognition.
author:
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Patrick
full_name: Hanebrink, Patrick
last_name: Hanebrink
- first_name: Lukas
full_name: Drude, Lukas
id: '11213'
last_name: Drude
- 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
citation:
ama: 'Boeddeker C, Hanebrink P, Drude L, Heymann J, Haeb-Umbach R. Optimizing Neural-Network
Supported Acoustic Beamforming by Algorithmic Differentiation. In: Proc. IEEE
Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP). ; 2017.'
apa: Boeddeker, C., Hanebrink, P., Drude, L., Heymann, J., & Haeb-Umbach, R.
(2017). Optimizing Neural-Network Supported Acoustic Beamforming by Algorithmic
Differentiation. In Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal
Processing (ICASSP).
bibtex: '@inproceedings{Boeddeker_Hanebrink_Drude_Heymann_Haeb-Umbach_2017, title={Optimizing
Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation},
booktitle={Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)},
author={Boeddeker, Christoph and Hanebrink, Patrick and Drude, Lukas and Heymann,
Jahn and Haeb-Umbach, Reinhold}, year={2017} }'
chicago: Boeddeker, Christoph, Patrick Hanebrink, Lukas Drude, Jahn Heymann, and
Reinhold Haeb-Umbach. “Optimizing Neural-Network Supported Acoustic Beamforming
by Algorithmic Differentiation.” In Proc. IEEE Intl. Conf. on Acoustics, Speech
and Signal Processing (ICASSP), 2017.
ieee: C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, and R. Haeb-Umbach, “Optimizing
Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation,”
in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP),
2017.
mla: Boeddeker, Christoph, et al. “Optimizing Neural-Network Supported Acoustic
Beamforming by Algorithmic Differentiation.” Proc. IEEE Intl. Conf. on Acoustics,
Speech and Signal Processing (ICASSP), 2017.
short: 'C. Boeddeker, P. Hanebrink, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc.
IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.'
date_created: 2019-07-12T05:27:16Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/icassp_2017_boeddeker_paper.pdf
oa: '1'
publication: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
status: public
title: Optimizing Neural-Network Supported Acoustic Beamforming by Algorithmic Differentiation
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11737'
abstract:
- lang: eng
text: The benefits of both a logarithmic spectral amplitude (LSA) estimation and
a modeling in a generalized spectral domain (where short-time amplitudes are raised
to a generalized power exponent, not restricted to magnitude or power spectrum)
are combined in this contribution to achieve a better tradeoff between speech
quality and noise suppression in single-channel speech enhancement. A novel gain
function is derived to enhance the logarithmic generalized spectral amplitudes
of noisy speech. Experiments on the CHiME-3 dataset show that it outperforms the
famous minimum mean squared error (MMSE) LSA gain function of Ephraim and Malah
in terms of noise suppression by 1.4 dB, while the good speech quality of the
MMSE-LSA estimator is maintained.
author:
- first_name: Alleksej
full_name: Chinaev, Alleksej
last_name: Chinaev
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Chinaev A, Haeb-Umbach R. A Generalized Log-Spectral Amplitude Estimator for
Single-Channel Speech Enhancement. In: Proc. IEEE Intl. Conf. on Acoustics,
Speech and Signal Processing (ICASSP). ; 2017.'
apa: Chinaev, A., & Haeb-Umbach, R. (2017). A Generalized Log-Spectral Amplitude
Estimator for Single-Channel Speech Enhancement. In Proc. IEEE Intl. Conf.
on Acoustics, Speech and Signal Processing (ICASSP).
bibtex: '@inproceedings{Chinaev_Haeb-Umbach_2017, title={A Generalized Log-Spectral
Amplitude Estimator for Single-Channel Speech Enhancement}, booktitle={Proc. IEEE
Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)}, author={Chinaev,
Alleksej and Haeb-Umbach, Reinhold}, year={2017} }'
chicago: Chinaev, Alleksej, and Reinhold Haeb-Umbach. “A Generalized Log-Spectral
Amplitude Estimator for Single-Channel Speech Enhancement.” In Proc. IEEE Intl.
Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.
ieee: A. Chinaev and R. Haeb-Umbach, “A Generalized Log-Spectral Amplitude Estimator
for Single-Channel Speech Enhancement,” in Proc. IEEE Intl. Conf. on Acoustics,
Speech and Signal Processing (ICASSP), 2017.
mla: Chinaev, Alleksej, and Reinhold Haeb-Umbach. “A Generalized Log-Spectral Amplitude
Estimator for Single-Channel Speech Enhancement.” Proc. IEEE Intl. Conf. on
Acoustics, Speech and Signal Processing (ICASSP), 2017.
short: 'A. Chinaev, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics, Speech
and Signal Processing (ICASSP), 2017.'
date_created: 2019-07-12T05:27:17Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/ChinHaeb17.pdf
oa: '1'
publication: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
related_material:
link:
- description: Slides
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2017/ChinHaeb17_Slides.pdf
status: public
title: A Generalized Log-Spectral Amplitude Estimator for Single-Channel Speech Enhancement
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11754'
abstract:
- lang: eng
text: Recent advances in discriminatively trained mask estimation networks to extract
a single source utilizing beamforming techniques demonstrate, that the integration
of statistical models and deep neural networks (DNNs) are a promising approach
for robust automatic speech recognition (ASR) applications. In this contribution
we demonstrate how discriminatively trained embeddings on spectral features can
be tightly integrated into statistical model-based source separation to separate
and transcribe overlapping speech. Good generalization to unseen spatial configurations
is achieved by estimating a statistical model at test time, while still leveraging
discriminative training of deep clustering embeddings on a separate training set.
We formulate an expectation maximization (EM) algorithm which jointly estimates
a model for deep clustering embeddings and complex-valued spatial observations
in the short time Fourier transform (STFT) domain at test time. Extensive simulations
confirm, that the integrated model outperforms (a) a deep clustering model with
a subsequent beamforming step and (b) an EM-based model with a beamforming step
alone in terms of signal to distortion ratio (SDR) and perceptually motivated
metric (PESQ) gains. ASR results on a reverberated dataset further show, that
the aforementioned gains translate to reduced word error rates (WERs) even in
reverberant environments.
author:
- first_name: Lukas
full_name: Drude, Lukas
id: '11213'
last_name: Drude
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Drude L, Haeb-Umbach R. Tight integration of spatial and spectral features
for BSS with Deep Clustering embeddings. In: INTERSPEECH 2017, Stockholm, Schweden.
; 2017.'
apa: Drude, L., & Haeb-Umbach, R. (2017). Tight integration of spatial and spectral
features for BSS with Deep Clustering embeddings. In INTERSPEECH 2017, Stockholm,
Schweden.
bibtex: '@inproceedings{Drude_Haeb-Umbach_2017, title={Tight integration of spatial
and spectral features for BSS with Deep Clustering embeddings}, booktitle={INTERSPEECH
2017, Stockholm, Schweden}, author={Drude, Lukas and Haeb-Umbach, Reinhold}, year={2017}
}'
chicago: Drude, Lukas, and Reinhold Haeb-Umbach. “Tight Integration of Spatial and
Spectral Features for BSS with Deep Clustering Embeddings.” In INTERSPEECH
2017, Stockholm, Schweden, 2017.
ieee: L. Drude and R. Haeb-Umbach, “Tight integration of spatial and spectral features
for BSS with Deep Clustering embeddings,” in INTERSPEECH 2017, Stockholm, Schweden,
2017.
mla: Drude, Lukas, and Reinhold Haeb-Umbach. “Tight Integration of Spatial and Spectral
Features for BSS with Deep Clustering Embeddings.” INTERSPEECH 2017, Stockholm,
Schweden, 2017.
short: 'L. Drude, R. Haeb-Umbach, in: INTERSPEECH 2017, Stockholm, Schweden, 2017.'
date_created: 2019-07-12T05:27:37Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Drude_paper.pdf
oa: '1'
publication: INTERSPEECH 2017, Stockholm, Schweden
related_material:
link:
- description: Slides
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Drude_slides.pdf
status: public
title: Tight integration of spatial and spectral features for BSS with Deep Clustering
embeddings
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '11770'
abstract:
- lang: eng
text: 'In this contribution we show how to exploit text data to support word discovery
from audio input in an underresourced target language. Given audio, of which a
certain amount is transcribed at the word level, and additional unrelated text
data, the approach is able to learn a probabilistic mapping from acoustic units
to characters and utilize it to segment the audio data into words without the
need of a pronunciation dictionary. This is achieved by three components: an unsupervised
acoustic unit discovery system, a supervisedly trained acoustic unit-to-grapheme
converter, and a word discovery system, which is initialized with a language model
trained on the text data. Experiments for multiple setups show that the initialization
of the language model with text data improves the word segementation performance
by a large margin.'
author:
- first_name: Thomas
full_name: Glarner, Thomas
id: '14169'
last_name: Glarner
- first_name: Benedikt
full_name: Boenninghoff, Benedikt
last_name: Boenninghoff
- first_name: Oliver
full_name: Walter, Oliver
last_name: Walter
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Glarner T, Boenninghoff B, Walter O, Haeb-Umbach R. Leveraging Text Data for
Word Segmentation for Underresourced Languages. In: INTERSPEECH 2017, Stockholm,
Schweden. ; 2017.'
apa: Glarner, T., Boenninghoff, B., Walter, O., & Haeb-Umbach, R. (2017). Leveraging
Text Data for Word Segmentation for Underresourced Languages. In INTERSPEECH
2017, Stockholm, Schweden.
bibtex: '@inproceedings{Glarner_Boenninghoff_Walter_Haeb-Umbach_2017, title={Leveraging
Text Data for Word Segmentation for Underresourced Languages}, booktitle={INTERSPEECH
2017, Stockholm, Schweden}, author={Glarner, Thomas and Boenninghoff, Benedikt
and Walter, Oliver and Haeb-Umbach, Reinhold}, year={2017} }'
chicago: Glarner, Thomas, Benedikt Boenninghoff, Oliver Walter, and Reinhold Haeb-Umbach.
“Leveraging Text Data for Word Segmentation for Underresourced Languages.” In
INTERSPEECH 2017, Stockholm, Schweden, 2017.
ieee: T. Glarner, B. Boenninghoff, O. Walter, and R. Haeb-Umbach, “Leveraging Text
Data for Word Segmentation for Underresourced Languages,” in INTERSPEECH 2017,
Stockholm, Schweden, 2017.
mla: Glarner, Thomas, et al. “Leveraging Text Data for Word Segmentation for Underresourced
Languages.” INTERSPEECH 2017, Stockholm, Schweden, 2017.
short: 'T. Glarner, B. Boenninghoff, O. Walter, R. Haeb-Umbach, in: INTERSPEECH
2017, Stockholm, Schweden, 2017.'
date_created: 2019-07-12T05:27:55Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Glarner_paper.pdf
oa: '1'
publication: INTERSPEECH 2017, Stockholm, Schweden
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2017/INTERSPEECH_2017_Glarner_poster.pdf
status: public
title: Leveraging Text Data for Word Segmentation for Underresourced Languages
type: conference
user_id: '44006'
year: '2017'
...
---
_id: '1180'
abstract:
- lang: eng
text: These days, there is a strong rise in the needs for machine learning applications,
requiring an automation of machine learning engineering which is referred to as
AutoML. In AutoML the selection, composition and parametrization of machine learning
algorithms is automated and tailored to a specific problem, resulting in a machine
learning pipeline. Current approaches reduce the AutoML problem to optimization
of hyperparameters. Based on recursive task networks, in this paper we present
one approach from the field of automated planning and one evolutionary optimization
approach. Instead of simply parametrizing a given pipeline, this allows for structure
optimization of machine learning pipelines, as well. We evaluate the two approaches
in an extensive evaluation, finding both approaches to have their strengths in
different areas. Moreover, the two approaches outperform the state-of-the-art
tool Auto-WEKA in many settings.
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Felix
full_name: Mohr, Felix
last_name: Mohr
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierachical Planning
Versus Evolutionary Optimization. In: 27th Workshop Computational Intelligence.
Dortmund; 2017.'
apa: 'Wever, M. D., Mohr, F., & Hüllermeier, E. (2017). Automatic Machine Learning:
Hierachical Planning Versus Evolutionary Optimization. In 27th Workshop Computational
Intelligence. Dortmund.'
bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2017, place={Dortmund}, title={Automatic
Machine Learning: Hierachical Planning Versus Evolutionary Optimization}, booktitle={27th
Workshop Computational Intelligence}, author={Wever, Marcel Dominik and Mohr,
Felix and Hüllermeier, Eyke}, year={2017} }'
chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automatic Machine
Learning: Hierachical Planning Versus Evolutionary Optimization.” In 27th Workshop
Computational Intelligence. Dortmund, 2017.'
ieee: 'M. D. Wever, F. Mohr, and E. Hüllermeier, “Automatic Machine Learning: Hierachical
Planning Versus Evolutionary Optimization,” in 27th Workshop Computational
Intelligence, Dortmund, 2017.'
mla: 'Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning
Versus Evolutionary Optimization.” 27th Workshop Computational Intelligence,
2017.'
short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence,
Dortmund, 2017.'
conference:
end_date: 2017-11-24
location: Dortmund
name: 27th Workshop Computational Intelligence
start_date: 2017-11-23
date_created: 2018-02-22T07:19:18Z
date_updated: 2022-01-06T06:51:09Z
ddc:
- '000'
department:
- _id: '355'
file:
- access_level: closed
content_type: application/pdf
creator: wever
date_created: 2018-11-06T15:28:09Z
date_updated: 2018-11-06T15:28:09Z
file_id: '5387'
file_name: CI Workshop AutoML.pdf
file_size: 323589
relation: main_file
success: 1
file_date_updated: 2018-11-06T15:28:09Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://publikationen.bibliothek.kit.edu/1000074341/4643874
oa: '1'
place: Dortmund
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '10'
name: SFB 901 - Subproject B2
publication: 27th Workshop Computational Intelligence
publication_status: published
status: public
title: 'Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization'
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '11809'
abstract:
- lang: eng
text: This paper presents an end-to-end training approach for a beamformer-supported
multi-channel ASR system. A neural network which estimates masks for a statistically
optimum beamformer is jointly trained with a network for acoustic modeling. To
update its parameters, we propagate the gradients from the acoustic model all
the way through feature extraction and the complex valued beamforming operation.
Besides avoiding a mismatch between the front-end and the back-end, this approach
also eliminates the need for stereo data, i.e., the parallel availability of clean
and noisy versions of the signals. Instead, it can be trained with real noisy
multichannel data only. Also, relying on the signal statistics for beamforming,
the approach makes no assumptions on the configuration of the microphone array.
We further observe a performance gain through joint training in terms of word
error rate in an evaluation of the system on the CHiME 4 dataset.
author:
- first_name: Jahn
full_name: Heymann, Jahn
id: '9168'
last_name: Heymann
- first_name: Lukas
full_name: Drude, Lukas
id: '11213'
last_name: Drude
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Patrick
full_name: Hanebrink, Patrick
last_name: Hanebrink
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Heymann J, Drude L, Boeddeker C, Hanebrink P, Haeb-Umbach R. BEAMNET: End-to-End
Training of a Beamformer-Supported Multi-Channel ASR System. In: Proc. IEEE
Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP). ; 2017.'
apa: 'Heymann, J., Drude, L., Boeddeker, C., Hanebrink, P., & Haeb-Umbach, R.
(2017). BEAMNET: End-to-End Training of a Beamformer-Supported Multi-Channel ASR
System. In Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing
(ICASSP).'
bibtex: '@inproceedings{Heymann_Drude_Boeddeker_Hanebrink_Haeb-Umbach_2017, title={BEAMNET:
End-to-End Training of a Beamformer-Supported Multi-Channel ASR System}, booktitle={Proc.
IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)}, author={Heymann,
Jahn and Drude, Lukas and Boeddeker, Christoph and Hanebrink, Patrick and Haeb-Umbach,
Reinhold}, year={2017} }'
chicago: 'Heymann, Jahn, Lukas Drude, Christoph Boeddeker, Patrick Hanebrink, and
Reinhold Haeb-Umbach. “BEAMNET: End-to-End Training of a Beamformer-Supported
Multi-Channel ASR System.” In Proc. IEEE Intl. Conf. on Acoustics, Speech and
Signal Processing (ICASSP), 2017.'
ieee: 'J. Heymann, L. Drude, C. Boeddeker, P. Hanebrink, and R. Haeb-Umbach, “BEAMNET:
End-to-End Training of a Beamformer-Supported Multi-Channel ASR System,” in Proc.
IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.'
mla: 'Heymann, Jahn, et al. “BEAMNET: End-to-End Training of a Beamformer-Supported
Multi-Channel ASR System.” Proc. IEEE Intl. Conf. on Acoustics, Speech and
Signal Processing (ICASSP), 2017.'
short: 'J. Heymann, L. Drude, C. Boeddeker, P. Hanebrink, R. Haeb-Umbach, in: Proc.
IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2017.'
date_created: 2019-07-12T05:28:40Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/icassp_2017_heymann_paper.pdf
oa: '1'
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2017/icassp_2017_heymann_poster.pdf
status: public
title: 'BEAMNET: End-to-End Training of a Beamformer-Supported Multi-Channel ASR System'
type: conference
user_id: '40767'
year: '2017'
...
---
_id: '11811'
abstract:
- lang: eng
text: 'Acoustic beamforming can greatly improve the performance of Automatic Speech
Recognition (ASR) and speech enhancement systems when multiple channels are available.
We recently proposed a way to support the model-based Generalized Eigenvalue beamforming
operation with a powerful neural network for spectral mask estimation. The enhancement
system has a number of desirable properties. In particular, neither assumptions
need to be made about the nature of the acoustic transfer function (e.g., being
anechonic), nor does the array configuration need to be known. While the system
has been originally developed to enhance speech in noisy environments, we show
in this article that it is also effective in suppressing reverberation, thus leading
to a generic trainable multi-channel speech enhancement system for robust speech
processing. To support this claim, we consider two distinct datasets: The CHiME
3 challenge, which features challenging real-world noise distortions, and the
Reverb challenge, which focuses on distortions caused by reverberation. We evaluate
the system both with respect to a speech enhancement and a recognition task. For
the first task we propose a new way to cope with the distortions introduced by
the Generalized Eigenvalue beamformer by renormalizing the target energy for each
frequency bin, and measure its effectiveness in terms of the PESQ score. For the
latter we feed the enhanced signal to a strong DNN back-end and achieve state-of-the-art
ASR results on both datasets. We further experiment with different network architectures
for spectral mask estimation: One small feed-forward network with only one hidden
layer, one Convolutional Neural Network and one bi-directional Long Short-Term
Memory network, showing that even a small network is capable of delivering significant
performance improvements.'
author:
- first_name: Jahn
full_name: Heymann, Jahn
id: '9168'
last_name: Heymann
- first_name: Lukas
full_name: Drude, Lukas
id: '11213'
last_name: Drude
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Heymann J, Drude L, Haeb-Umbach R. A Generic Neural Acoustic Beamforming Architecture
for Robust Multi-Channel Speech Processing. Computer Speech and Language.
2017.
apa: Heymann, J., Drude, L., & Haeb-Umbach, R. (2017). A Generic Neural Acoustic
Beamforming Architecture for Robust Multi-Channel Speech Processing. Computer
Speech and Language.
bibtex: '@article{Heymann_Drude_Haeb-Umbach_2017, title={A Generic Neural Acoustic
Beamforming Architecture for Robust Multi-Channel Speech Processing}, journal={Computer
Speech and Language}, author={Heymann, Jahn and Drude, Lukas and Haeb-Umbach,
Reinhold}, year={2017} }'
chicago: Heymann, Jahn, Lukas Drude, and Reinhold Haeb-Umbach. “A Generic Neural
Acoustic Beamforming Architecture for Robust Multi-Channel Speech Processing.”
Computer Speech and Language, 2017.
ieee: J. Heymann, L. Drude, and R. Haeb-Umbach, “A Generic Neural Acoustic Beamforming
Architecture for Robust Multi-Channel Speech Processing,” Computer Speech and
Language, 2017.
mla: Heymann, Jahn, et al. “A Generic Neural Acoustic Beamforming Architecture for
Robust Multi-Channel Speech Processing.” Computer Speech and Language,
2017.
short: J. Heymann, L. Drude, R. Haeb-Umbach, Computer Speech and Language (2017).
date_created: 2019-07-12T05:28:43Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2017/ComputerSpeechLanguage_2017_heymann_paper.pdf
oa: '1'
publication: Computer Speech and Language
status: public
title: A Generic Neural Acoustic Beamforming Architecture for Robust Multi-Channel
Speech Processing
type: journal_article
user_id: '44006'
year: '2017'
...
---
_id: '11984'
author:
- first_name: Bastian
full_name: Bloessl, Bastian
last_name: Bloessl
- first_name: Michele
full_name: Segata, Michele
last_name: Segata
- first_name: Christoph
full_name: Sommer, Christoph
id: '49154'
last_name: Sommer
orcid: 0000-0002-4336-7350
- first_name: Falko
full_name: Dressler, Falko
last_name: Dressler
citation:
ama: Bloessl B, Segata M, Sommer C, Dressler F. Performance Assessment of IEEE 802.11p
with an Open Source SDR-Based Prototype. IEEE Transactions on Mobile Computing.
2017:1162-1175. doi:10.1109/tmc.2017.2751474
apa: Bloessl, B., Segata, M., Sommer, C., & Dressler, F. (2017). Performance
Assessment of IEEE 802.11p with an Open Source SDR-Based Prototype. IEEE Transactions
on Mobile Computing, 1162–1175. https://doi.org/10.1109/tmc.2017.2751474
bibtex: '@article{Bloessl_Segata_Sommer_Dressler_2017, title={Performance Assessment
of IEEE 802.11p with an Open Source SDR-Based Prototype}, DOI={10.1109/tmc.2017.2751474},
journal={IEEE Transactions on Mobile Computing}, author={Bloessl, Bastian and
Segata, Michele and Sommer, Christoph and Dressler, Falko}, year={2017}, pages={1162–1175}
}'
chicago: Bloessl, Bastian, Michele Segata, Christoph Sommer, and Falko Dressler.
“Performance Assessment of IEEE 802.11p with an Open Source SDR-Based Prototype.”
IEEE Transactions on Mobile Computing, 2017, 1162–75. https://doi.org/10.1109/tmc.2017.2751474.
ieee: B. Bloessl, M. Segata, C. Sommer, and F. Dressler, “Performance Assessment
of IEEE 802.11p with an Open Source SDR-Based Prototype,” IEEE Transactions
on Mobile Computing, pp. 1162–1175, 2017.
mla: Bloessl, Bastian, et al. “Performance Assessment of IEEE 802.11p with an Open
Source SDR-Based Prototype.” IEEE Transactions on Mobile Computing, 2017,
pp. 1162–75, doi:10.1109/tmc.2017.2751474.
short: B. Bloessl, M. Segata, C. Sommer, F. Dressler, IEEE Transactions on Mobile
Computing (2017) 1162–1175.
date_created: 2019-07-18T09:51:46Z
date_updated: 2022-01-06T06:51:15Z
department:
- _id: '589'
doi: 10.1109/tmc.2017.2751474
language:
- iso: eng
page: 1162-1175
publication: IEEE Transactions on Mobile Computing
publication_identifier:
issn:
- 1536-1233
publication_status: published
status: public
title: Performance Assessment of IEEE 802.11p with an Open Source SDR-Based Prototype
type: journal_article
user_id: '49154'
year: '2017'
...
---
_id: '120'
abstract:
- lang: eng
text: 'Within software engineering, requirements engineering starts from imprecise
and vague user requirements descriptions and infers precise, formalized specifications.
Techniques, such as interviewing by requirements engineers, are typically applied
to identify the user’s needs. We want to partially automate even this first step
of requirements elicitation by methods of evolutionary computation. The idea is
to enable users to specify their desired software by listing examples of behavioral
descriptions. Users initially specify two lists of operation sequences, one with
desired behaviors and one with forbidden behaviors. Then, we search for the appropriate
formal software specification in the form of a deterministic finite automaton.
We solve this problem known as grammatical inference with an active coevolutionary
approach following Bongard and Lipson [2]. The coevolutionary process alternates
between two phases: (A) additional training data is actively proposed by an evolutionary
process and the user is interactively asked to label it; (B) appropriate automata
are then evolved to solve this extended grammatical inference problem. Our approach
leverages multi-objective evolution in both phases and outperforms the state-of-the-art
technique [2] for input alphabet sizes of three and more, which are relevant to
our problem domain of requirements specification.'
author:
- first_name: Marcel Dominik
full_name: Wever, Marcel Dominik
id: '33176'
last_name: Wever
orcid: ' https://orcid.org/0000-0001-9782-6818'
- first_name: Lorijn
full_name: van Rooijen, Lorijn
id: '58843'
last_name: van Rooijen
- first_name: Heiko
full_name: Hamann, Heiko
last_name: Hamann
citation:
ama: 'Wever MD, van Rooijen L, Hamann H. Active Coevolutionary Learning of Requirements
Specifications from Examples. In: Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO). ; 2017:1327--1334. doi:10.1145/3071178.3071258'
apa: Wever, M. D., van Rooijen, L., & Hamann, H. (2017). Active Coevolutionary
Learning of Requirements Specifications from Examples. In Proceedings of the
Genetic and Evolutionary Computation Conference (GECCO) (pp. 1327--1334).
https://doi.org/10.1145/3071178.3071258
bibtex: '@inproceedings{Wever_van Rooijen_Hamann_2017, title={Active Coevolutionary
Learning of Requirements Specifications from Examples}, DOI={10.1145/3071178.3071258},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference
(GECCO)}, author={Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko},
year={2017}, pages={1327--1334} }'
chicago: Wever, Marcel Dominik, Lorijn van Rooijen, and Heiko Hamann. “Active Coevolutionary
Learning of Requirements Specifications from Examples.” In Proceedings of the
Genetic and Evolutionary Computation Conference (GECCO), 1327--1334, 2017.
https://doi.org/10.1145/3071178.3071258.
ieee: M. D. Wever, L. van Rooijen, and H. Hamann, “Active Coevolutionary Learning
of Requirements Specifications from Examples,” in Proceedings of the Genetic
and Evolutionary Computation Conference (GECCO), 2017, pp. 1327--1334.
mla: Wever, Marcel Dominik, et al. “Active Coevolutionary Learning of Requirements
Specifications from Examples.” Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO), 2017, pp. 1327--1334, doi:10.1145/3071178.3071258.
short: 'M.D. Wever, L. van Rooijen, H. Hamann, in: Proceedings of the Genetic and
Evolutionary Computation Conference (GECCO), 2017, pp. 1327--1334.'
date_created: 2017-10-17T12:41:15Z
date_updated: 2022-01-06T06:51:15Z
ddc:
- '000'
department:
- _id: '66'
doi: 10.1145/3071178.3071258
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T15:00:35Z
date_updated: 2018-11-02T15:00:35Z
file_id: '5290'
file_name: p1327-wever.pdf
file_size: 1092021
relation: main_file
success: 1
file_date_updated: 2018-11-02T15:00:35Z
has_accepted_license: '1'
language:
- iso: eng
page: 1327--1334
project:
- _id: '1'
name: SFB 901
- _id: '9'
name: SFB 901 - Subproject B1
- _id: '3'
name: SFB 901 - Project Area B
publication: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)
status: public
title: Active Coevolutionary Learning of Requirements Specifications from Examples
type: conference
user_id: '477'
year: '2017'
...
---
_id: '12005'
author:
- first_name: David
full_name: Eckhoff, David
last_name: Eckhoff
- first_name: Alexander
full_name: Brummer, Alexander
last_name: Brummer
- first_name: Christoph
full_name: Sommer, Christoph
id: '49154'
last_name: Sommer
orcid: 0000-0002-4336-7350
citation:
ama: 'Eckhoff D, Brummer A, Sommer C. On the impact of antenna patterns on VANET
simulation. In: 2016 IEEE Vehicular Networking Conference (VNC). ; 2017.
doi:10.1109/vnc.2016.7835925'
apa: Eckhoff, D., Brummer, A., & Sommer, C. (2017). On the impact of antenna
patterns on VANET simulation. In 2016 IEEE Vehicular Networking Conference
(VNC). https://doi.org/10.1109/vnc.2016.7835925
bibtex: '@inproceedings{Eckhoff_Brummer_Sommer_2017, title={On the impact of antenna
patterns on VANET simulation}, DOI={10.1109/vnc.2016.7835925},
booktitle={2016 IEEE Vehicular Networking Conference (VNC)}, author={Eckhoff,
David and Brummer, Alexander and Sommer, Christoph}, year={2017} }'
chicago: Eckhoff, David, Alexander Brummer, and Christoph Sommer. “On the Impact
of Antenna Patterns on VANET Simulation.” In 2016 IEEE Vehicular Networking
Conference (VNC), 2017. https://doi.org/10.1109/vnc.2016.7835925.
ieee: D. Eckhoff, A. Brummer, and C. Sommer, “On the impact of antenna patterns
on VANET simulation,” in 2016 IEEE Vehicular Networking Conference (VNC),
2017.
mla: Eckhoff, David, et al. “On the Impact of Antenna Patterns on VANET Simulation.”
2016 IEEE Vehicular Networking Conference (VNC), 2017, doi:10.1109/vnc.2016.7835925.
short: 'D. Eckhoff, A. Brummer, C. Sommer, in: 2016 IEEE Vehicular Networking Conference
(VNC), 2017.'
date_created: 2019-07-18T09:52:50Z
date_updated: 2022-01-06T06:51:15Z
department:
- _id: '589'
doi: 10.1109/vnc.2016.7835925
language:
- iso: eng
publication: 2016 IEEE Vehicular Networking Conference (VNC)
publication_identifier:
isbn:
- '9781509051977'
publication_status: published
status: public
title: On the impact of antenna patterns on VANET simulation
type: conference
user_id: '49154'
year: '2017'
...
---
_id: '12006'
author:
- first_name: David
full_name: Eckhoff, David
last_name: Eckhoff
- first_name: Christoph
full_name: Sommer, Christoph
id: '49154'
last_name: Sommer
orcid: 0000-0002-4336-7350
citation:
ama: 'Eckhoff D, Sommer C. Marrying safety with privacy: A holistic solution for
location privacy in VANETs. In: 2016 IEEE Vehicular Networking Conference (VNC).
; 2017. doi:10.1109/vnc.2016.7835971'
apa: 'Eckhoff, D., & Sommer, C. (2017). Marrying safety with privacy: A holistic
solution for location privacy in VANETs. In 2016 IEEE Vehicular Networking
Conference (VNC). https://doi.org/10.1109/vnc.2016.7835971'
bibtex: '@inproceedings{Eckhoff_Sommer_2017, title={Marrying safety with privacy:
A holistic solution for location privacy in VANETs}, DOI={10.1109/vnc.2016.7835971},
booktitle={2016 IEEE Vehicular Networking Conference (VNC)}, author={Eckhoff,
David and Sommer, Christoph}, year={2017} }'
chicago: 'Eckhoff, David, and Christoph Sommer. “Marrying Safety with Privacy: A
Holistic Solution for Location Privacy in VANETs.” In 2016 IEEE Vehicular Networking
Conference (VNC), 2017. https://doi.org/10.1109/vnc.2016.7835971.'
ieee: 'D. Eckhoff and C. Sommer, “Marrying safety with privacy: A holistic solution
for location privacy in VANETs,” in 2016 IEEE Vehicular Networking Conference
(VNC), 2017.'
mla: 'Eckhoff, David, and Christoph Sommer. “Marrying Safety with Privacy: A Holistic
Solution for Location Privacy in VANETs.” 2016 IEEE Vehicular Networking Conference
(VNC), 2017, doi:10.1109/vnc.2016.7835971.'
short: 'D. Eckhoff, C. Sommer, in: 2016 IEEE Vehicular Networking Conference (VNC),
2017.'
date_created: 2019-07-18T09:52:53Z
date_updated: 2022-01-06T06:51:15Z
department:
- _id: '589'
doi: 10.1109/vnc.2016.7835971
language:
- iso: eng
publication: 2016 IEEE Vehicular Networking Conference (VNC)
publication_identifier:
isbn:
- '9781509051977'
publication_status: published
status: public
title: 'Marrying safety with privacy: A holistic solution for location privacy in
VANETs'
type: conference
user_id: '49154'
year: '2017'
...
---
_id: '12014'
author:
- first_name: Florian
full_name: Hagenauer, Florian
last_name: Hagenauer
- first_name: Christoph
full_name: Sommer, Christoph
id: '49154'
last_name: Sommer
orcid: 0000-0002-4336-7350
- first_name: Takamasa
full_name: Higuchi, Takamasa
last_name: Higuchi
- first_name: Onur
full_name: Altintas, Onur
last_name: Altintas
- first_name: Falko
full_name: Dressler, Falko
last_name: Dressler
citation:
ama: 'Hagenauer F, Sommer C, Higuchi T, Altintas O, Dressler F. Poster: Using clusters
of parked cars as virtual vehicular network infrastructure. In: 2016 IEEE Vehicular
Networking Conference (VNC). ; 2017. doi:10.1109/vnc.2016.7835943'
apa: 'Hagenauer, F., Sommer, C., Higuchi, T., Altintas, O., & Dressler, F. (2017).
Poster: Using clusters of parked cars as virtual vehicular network infrastructure.
In 2016 IEEE Vehicular Networking Conference (VNC). https://doi.org/10.1109/vnc.2016.7835943'
bibtex: '@inproceedings{Hagenauer_Sommer_Higuchi_Altintas_Dressler_2017, title={Poster:
Using clusters of parked cars as virtual vehicular network infrastructure}, DOI={10.1109/vnc.2016.7835943},
booktitle={2016 IEEE Vehicular Networking Conference (VNC)}, author={Hagenauer,
Florian and Sommer, Christoph and Higuchi, Takamasa and Altintas, Onur and Dressler,
Falko}, year={2017} }'
chicago: 'Hagenauer, Florian, Christoph Sommer, Takamasa Higuchi, Onur Altintas,
and Falko Dressler. “Poster: Using Clusters of Parked Cars as Virtual Vehicular
Network Infrastructure.” In 2016 IEEE Vehicular Networking Conference (VNC),
2017. https://doi.org/10.1109/vnc.2016.7835943.'
ieee: 'F. Hagenauer, C. Sommer, T. Higuchi, O. Altintas, and F. Dressler, “Poster:
Using clusters of parked cars as virtual vehicular network infrastructure,” in
2016 IEEE Vehicular Networking Conference (VNC), 2017.'
mla: 'Hagenauer, Florian, et al. “Poster: Using Clusters of Parked Cars as Virtual
Vehicular Network Infrastructure.” 2016 IEEE Vehicular Networking Conference
(VNC), 2017, doi:10.1109/vnc.2016.7835943.'
short: 'F. Hagenauer, C. Sommer, T. Higuchi, O. Altintas, F. Dressler, in: 2016
IEEE Vehicular Networking Conference (VNC), 2017.'
date_created: 2019-07-18T09:53:21Z
date_updated: 2022-01-06T06:51:15Z
department:
- _id: '589'
doi: 10.1109/vnc.2016.7835943
language:
- iso: eng
publication: 2016 IEEE Vehicular Networking Conference (VNC)
publication_identifier:
isbn:
- '9781509051977'
publication_status: published
status: public
title: 'Poster: Using clusters of parked cars as virtual vehicular network infrastructure'
type: conference
user_id: '49154'
year: '2017'
...
---
_id: '12015'
author:
- first_name: Florian
full_name: Hagenauer, Florian
last_name: Hagenauer
- first_name: Christoph
full_name: Sommer, Christoph
id: '49154'
last_name: Sommer
orcid: 0000-0002-4336-7350
- first_name: Takamasa
full_name: Higuchi, Takamasa
last_name: Higuchi
- first_name: Onur
full_name: Altintas, Onur
last_name: Altintas
- first_name: Falko
full_name: Dressler, Falko
last_name: Dressler
citation:
ama: 'Hagenauer F, Sommer C, Higuchi T, Altintas O, Dressler F. Parked Cars as Virtual
Network Infrastructure. In: Proceedings of the 2nd ACM International Workshop
on Smart, Autonomous, and Connected Vehicular Systems and Services - CarSys ’17.
; 2017. doi:10.1145/3131944.3131952'
apa: Hagenauer, F., Sommer, C., Higuchi, T., Altintas, O., & Dressler, F. (2017).
Parked Cars as Virtual Network Infrastructure. In Proceedings of the 2nd ACM
International Workshop on Smart, Autonomous, and Connected Vehicular Systems and
Services - CarSys ’17. https://doi.org/10.1145/3131944.3131952
bibtex: '@inproceedings{Hagenauer_Sommer_Higuchi_Altintas_Dressler_2017, title={Parked
Cars as Virtual Network Infrastructure}, DOI={10.1145/3131944.3131952},
booktitle={Proceedings of the 2nd ACM International Workshop on Smart, Autonomous,
and Connected Vehicular Systems and Services - CarSys ’17}, author={Hagenauer,
Florian and Sommer, Christoph and Higuchi, Takamasa and Altintas, Onur and Dressler,
Falko}, year={2017} }'
chicago: Hagenauer, Florian, Christoph Sommer, Takamasa Higuchi, Onur Altintas,
and Falko Dressler. “Parked Cars as Virtual Network Infrastructure.” In Proceedings
of the 2nd ACM International Workshop on Smart, Autonomous, and Connected Vehicular
Systems and Services - CarSys ’17, 2017. https://doi.org/10.1145/3131944.3131952.
ieee: F. Hagenauer, C. Sommer, T. Higuchi, O. Altintas, and F. Dressler, “Parked
Cars as Virtual Network Infrastructure,” in Proceedings of the 2nd ACM International
Workshop on Smart, Autonomous, and Connected Vehicular Systems and Services -
CarSys ’17, 2017.
mla: Hagenauer, Florian, et al. “Parked Cars as Virtual Network Infrastructure.”
Proceedings of the 2nd ACM International Workshop on Smart, Autonomous, and
Connected Vehicular Systems and Services - CarSys ’17, 2017, doi:10.1145/3131944.3131952.
short: 'F. Hagenauer, C. Sommer, T. Higuchi, O. Altintas, F. Dressler, in: Proceedings
of the 2nd ACM International Workshop on Smart, Autonomous, and Connected Vehicular
Systems and Services - CarSys ’17, 2017.'
date_created: 2019-07-18T09:53:23Z
date_updated: 2022-01-06T06:51:15Z
department:
- _id: '589'
doi: 10.1145/3131944.3131952
language:
- iso: eng
publication: Proceedings of the 2nd ACM International Workshop on Smart, Autonomous,
and Connected Vehicular Systems and Services - CarSys '17
publication_identifier:
isbn:
- '9781450351461'
publication_status: published
status: public
title: Parked Cars as Virtual Network Infrastructure
type: conference
user_id: '49154'
year: '2017'
...
---
_id: '12016'
author:
- first_name: Florian
full_name: Hagenauer, Florian
last_name: Hagenauer
- first_name: Christoph
full_name: Sommer, Christoph
id: '49154'
last_name: Sommer
orcid: 0000-0002-4336-7350
- first_name: Takamasa
full_name: Higuchi, Takamasa
last_name: Higuchi
- first_name: Onur
full_name: Altintas, Onur
last_name: Altintas
- first_name: Falko
full_name: Dressler, Falko
last_name: Dressler
citation:
ama: 'Hagenauer F, Sommer C, Higuchi T, Altintas O, Dressler F. Vehicular Micro
Clouds as Virtual Edge Servers for Efficient Data Collection. In: Proceedings
of the 2nd ACM International Workshop on Smart, Autonomous, and Connected Vehicular
Systems and Services - CarSys ’17. ; 2017. doi:10.1145/3131944.3133937'
apa: Hagenauer, F., Sommer, C., Higuchi, T., Altintas, O., & Dressler, F. (2017).
Vehicular Micro Clouds as Virtual Edge Servers for Efficient Data Collection.
In Proceedings of the 2nd ACM International Workshop on Smart, Autonomous,
and Connected Vehicular Systems and Services - CarSys ’17. https://doi.org/10.1145/3131944.3133937
bibtex: '@inproceedings{Hagenauer_Sommer_Higuchi_Altintas_Dressler_2017, title={Vehicular
Micro Clouds as Virtual Edge Servers for Efficient Data Collection}, DOI={10.1145/3131944.3133937},
booktitle={Proceedings of the 2nd ACM International Workshop on Smart, Autonomous,
and Connected Vehicular Systems and Services - CarSys ’17}, author={Hagenauer,
Florian and Sommer, Christoph and Higuchi, Takamasa and Altintas, Onur and Dressler,
Falko}, year={2017} }'
chicago: Hagenauer, Florian, Christoph Sommer, Takamasa Higuchi, Onur Altintas,
and Falko Dressler. “Vehicular Micro Clouds as Virtual Edge Servers for Efficient
Data Collection.” In Proceedings of the 2nd ACM International Workshop on Smart,
Autonomous, and Connected Vehicular Systems and Services - CarSys ’17, 2017.
https://doi.org/10.1145/3131944.3133937.
ieee: F. Hagenauer, C. Sommer, T. Higuchi, O. Altintas, and F. Dressler, “Vehicular
Micro Clouds as Virtual Edge Servers for Efficient Data Collection,” in Proceedings
of the 2nd ACM International Workshop on Smart, Autonomous, and Connected Vehicular
Systems and Services - CarSys ’17, 2017.
mla: Hagenauer, Florian, et al. “Vehicular Micro Clouds as Virtual Edge Servers
for Efficient Data Collection.” Proceedings of the 2nd ACM International Workshop
on Smart, Autonomous, and Connected Vehicular Systems and Services - CarSys ’17,
2017, doi:10.1145/3131944.3133937.
short: 'F. Hagenauer, C. Sommer, T. Higuchi, O. Altintas, F. Dressler, in: Proceedings
of the 2nd ACM International Workshop on Smart, Autonomous, and Connected Vehicular
Systems and Services - CarSys ’17, 2017.'
date_created: 2019-07-18T09:53:26Z
date_updated: 2022-01-06T06:51:15Z
department:
- _id: '589'
doi: 10.1145/3131944.3133937
language:
- iso: eng
publication: Proceedings of the 2nd ACM International Workshop on Smart, Autonomous,
and Connected Vehicular Systems and Services - CarSys '17
publication_identifier:
isbn:
- '9781450351461'
publication_status: published
status: public
title: Vehicular Micro Clouds as Virtual Edge Servers for Efficient Data Collection
type: conference
user_id: '49154'
year: '2017'
...
---
_id: '12018'
author:
- first_name: Tobias
full_name: Hardes, Tobias
last_name: Hardes
- first_name: Falko
full_name: Dressler, Falko
last_name: Dressler
- first_name: Christoph
full_name: Sommer, Christoph
id: '49154'
last_name: Sommer
orcid: 0000-0002-4336-7350
citation:
ama: 'Hardes T, Dressler F, Sommer C. Simulating a city-scale community network:
From models to first improvements for Freifunk. In: 2017 International Conference
on Networked Systems (NetSys). ; 2017. doi:10.1109/netsys.2017.7903954'
apa: 'Hardes, T., Dressler, F., & Sommer, C. (2017). Simulating a city-scale
community network: From models to first improvements for Freifunk. In 2017
International Conference on Networked Systems (NetSys). https://doi.org/10.1109/netsys.2017.7903954'
bibtex: '@inproceedings{Hardes_Dressler_Sommer_2017, title={Simulating a city-scale
community network: From models to first improvements for Freifunk}, DOI={10.1109/netsys.2017.7903954},
booktitle={2017 International Conference on Networked Systems (NetSys)}, author={Hardes,
Tobias and Dressler, Falko and Sommer, Christoph}, year={2017} }'
chicago: 'Hardes, Tobias, Falko Dressler, and Christoph Sommer. “Simulating a City-Scale
Community Network: From Models to First Improvements for Freifunk.” In 2017
International Conference on Networked Systems (NetSys), 2017. https://doi.org/10.1109/netsys.2017.7903954.'
ieee: 'T. Hardes, F. Dressler, and C. Sommer, “Simulating a city-scale community
network: From models to first improvements for Freifunk,” in 2017 International
Conference on Networked Systems (NetSys), 2017.'
mla: 'Hardes, Tobias, et al. “Simulating a City-Scale Community Network: From Models
to First Improvements for Freifunk.” 2017 International Conference on Networked
Systems (NetSys), 2017, doi:10.1109/netsys.2017.7903954.'
short: 'T. Hardes, F. Dressler, C. Sommer, in: 2017 International Conference on
Networked Systems (NetSys), 2017.'
date_created: 2019-07-18T09:53:31Z
date_updated: 2022-01-06T06:51:15Z
department:
- _id: '589'
doi: 10.1109/netsys.2017.7903954
language:
- iso: eng
publication: 2017 International Conference on Networked Systems (NetSys)
publication_identifier:
isbn:
- '9781509043941'
publication_status: published
status: public
title: 'Simulating a city-scale community network: From models to first improvements
for Freifunk'
type: conference
user_id: '49154'
year: '2017'
...