---
_id: '34123'
abstract:
- lang: eng
text: Through technological progress during recent years, Augmented Reality (AR)
technology can be used on ordinary smartphones with applications (Apps) in many
formal and informal learning environments and educational institutions (e.g. [1,
2]). It is emerging as a suitable technology for teaching psychomotor skills.
Simultaneously, gamification has become increasingly popular in the teaching field,
providing famous examples, such as Duolingo (for the acquisition of foreign languages)
or Codecademy (for learning programming languages) [3]. Many papers have already
highlighted the beneficial aspects of gamification and AR for education and teaching
(e.g. [1, 2, 4, 5]. While gamification is useful for improving students’ motivation
and engagement, AR can be applied to teach them operational skills without any
time, costs and place constraints. Hence, this opens up numerous possibilities
and forms to combine these two aspects (AR and gamification) for higher education
teaching. However, there has been less research focusing on how gamification and
AR can be combined in a useful manner to keep up students’ initial motivation
aroused through novelty effects of AR learning environments. Accordingly, this
paper will present such a gamification concept for an AR based virtual preparation
laboratory training to overcome the risk of demotivation, once AR will settle
as a mainstream technology such as learning videos. The focus of the AR-App –
presently being developed at the University of Paderborn – is to remedy the students’
lack of practical skills when operating electro-technical laboratory equipment
during their compulsory laboratory training.
author:
- first_name: Mesut
full_name: Alptekin, Mesut
id: '11763'
last_name: Alptekin
- first_name: Katrin
full_name: Temmen, Katrin
id: '30086'
last_name: Temmen
citation:
ama: 'Alptekin M, Temmen K. Gamification in an Augmented Reality Based Virtual Preparation
Laboratory Training. In: The Challenges of the Digital Transformation in Education.
Springer International Publishing; 2019. doi:10.1007/978-3-030-11932-4_54'
apa: Alptekin, M., & Temmen, K. (2019). Gamification in an Augmented Reality
Based Virtual Preparation Laboratory Training. In The Challenges of the Digital
Transformation in Education. International Conference on Interactive Collaborative
Learning and Engineering Pedagogy (ICL) 2018, Kos Island, Greece. Springer International
Publishing. https://doi.org/10.1007/978-3-030-11932-4_54
bibtex: '@inbook{Alptekin_Temmen_2019, place={Cham}, title={Gamification in an Augmented
Reality Based Virtual Preparation Laboratory Training}, DOI={10.1007/978-3-030-11932-4_54},
booktitle={The Challenges of the Digital Transformation in Education}, publisher={Springer
International Publishing}, author={Alptekin, Mesut and Temmen, Katrin}, year={2019}
}'
chicago: 'Alptekin, Mesut, and Katrin Temmen. “Gamification in an Augmented Reality
Based Virtual Preparation Laboratory Training.” In The Challenges of the Digital
Transformation in Education. Cham: Springer International Publishing, 2019.
https://doi.org/10.1007/978-3-030-11932-4_54.'
ieee: 'M. Alptekin and K. Temmen, “Gamification in an Augmented Reality Based Virtual
Preparation Laboratory Training,” in The Challenges of the Digital Transformation
in Education, Cham: Springer International Publishing, 2019.'
mla: Alptekin, Mesut, and Katrin Temmen. “Gamification in an Augmented Reality Based
Virtual Preparation Laboratory Training.” The Challenges of the Digital Transformation
in Education, Springer International Publishing, 2019, doi:10.1007/978-3-030-11932-4_54.
short: 'M. Alptekin, K. Temmen, in: The Challenges of the Digital Transformation
in Education, Springer International Publishing, Cham, 2019.'
conference:
end_date: 2018-09-28
location: Kos Island, Greece
name: International Conference on Interactive Collaborative Learning and Engineering
Pedagogy (ICL) 2018
start_date: 2018-09-25
date_created: 2022-11-22T11:32:35Z
date_updated: 2024-12-29T11:09:43Z
ddc:
- '000'
department:
- _id: '34'
- _id: '300'
doi: 10.1007/978-3-030-11932-4_54
file:
- access_level: closed
content_type: application/pdf
creator: mesutalp
date_created: 2024-12-29T11:07:54Z
date_updated: 2024-12-29T11:07:54Z
file_id: '57865'
file_name: fullpaper_camera_ready.pdf
file_size: 366224
relation: main_file
success: 1
file_date_updated: 2024-12-29T11:07:54Z
has_accepted_license: '1'
keyword:
- Augmented Reality
- Laboratory Training
- Engineering Education
- Gamification
language:
- iso: eng
place: Cham
publication: The Challenges of the Digital Transformation in Education
publication_identifier:
isbn:
- '9783030119317'
- '9783030119324'
issn:
- 2194-5357
- 2194-5365
publication_status: published
publisher: Springer International Publishing
status: public
title: Gamification in an Augmented Reality Based Virtual Preparation Laboratory Training
type: book_chapter
user_id: '11763'
year: '2019'
...
---
_id: '57889'
abstract:
- lang: eng
text: During the past decade, there has been an increase of pedagogical research
under conditions of posthuman theories, such as the Actor Network Theory or post-phenomenology.
Yet, there has not been much research on the materiality of music pedagogical
practices. This article introduces an ongoing grounded-theory study on the role
of things (e.g., music instruments, black board, or digital devices) within the
music classroom. Results from the analysis of group discussions and interviews
with student teachers show tensions between personal preferences, school conventions,
and material conventions within the process of introducing things into the classroom.
(DIPF/Orig.)
author:
- first_name: Marc
full_name: Godau, Marc
id: '98877'
last_name: Godau
citation:
ama: 'Godau M. Wie kommen die Dinge in den Musikunterricht? Zur Materialität musikpädagogischer
Praxis am Beispiel divergierender Orientierungen im Kontext unterrichtsbezogenen
Handelns angehender Lehrkräfte. In: Clausen B, Dreßler S, eds. Soziale Aspekte
Des Musiklernens. Musikpädagogische Forschung. Waxmann; 2018:43–55.'
apa: Godau, M. (2018). Wie kommen die Dinge in den Musikunterricht? Zur Materialität
musikpädagogischer Praxis am Beispiel divergierender Orientierungen im Kontext
unterrichtsbezogenen Handelns angehender Lehrkräfte. In B. Clausen & S. Dreßler
(Eds.), Soziale Aspekte des Musiklernens (pp. 43–55). Waxmann.
bibtex: '@inbook{Godau_2018, place={Münster, New York}, series={Musikpädagogische
Forschung}, title={Wie kommen die Dinge in den Musikunterricht? Zur Materialität
musikpädagogischer Praxis am Beispiel divergierender Orientierungen im Kontext
unterrichtsbezogenen Handelns angehender Lehrkräfte}, booktitle={Soziale Aspekte
des Musiklernens}, publisher={Waxmann}, author={Godau, Marc}, editor={Clausen,
Bernd and Dreßler, Susanne}, year={2018}, pages={43–55}, collection={Musikpädagogische
Forschung} }'
chicago: 'Godau, Marc. “Wie Kommen Die Dinge in Den Musikunterricht? Zur Materialität
Musikpädagogischer Praxis Am Beispiel Divergierender Orientierungen Im Kontext
Unterrichtsbezogenen Handelns Angehender Lehrkräfte.” In Soziale Aspekte Des
Musiklernens, edited by Bernd Clausen and Susanne Dreßler, 43–55. Musikpädagogische
Forschung. Münster, New York: Waxmann, 2018.'
ieee: 'M. Godau, “Wie kommen die Dinge in den Musikunterricht? Zur Materialität
musikpädagogischer Praxis am Beispiel divergierender Orientierungen im Kontext
unterrichtsbezogenen Handelns angehender Lehrkräfte,” in Soziale Aspekte des
Musiklernens, B. Clausen and S. Dreßler, Eds. Münster, New York: Waxmann,
2018, pp. 43–55.'
mla: Godau, Marc. “Wie Kommen Die Dinge in Den Musikunterricht? Zur Materialität
Musikpädagogischer Praxis Am Beispiel Divergierender Orientierungen Im Kontext
Unterrichtsbezogenen Handelns Angehender Lehrkräfte.” Soziale Aspekte Des Musiklernens,
edited by Bernd Clausen and Susanne Dreßler, Waxmann, 2018, pp. 43–55.
short: 'M. Godau, in: B. Clausen, S. Dreßler (Eds.), Soziale Aspekte Des Musiklernens,
Waxmann, Münster, New York, 2018, pp. 43–55.'
date_created: 2024-12-30T14:43:14Z
date_updated: 2025-02-06T10:52:25Z
department:
- _id: '131'
- _id: '36'
- _id: '129'
- _id: '540'
editor:
- first_name: Bernd
full_name: Clausen, Bernd
last_name: Clausen
- first_name: Susanne
full_name: Dreßler, Susanne
last_name: Dreßler
extern: '1'
keyword:
- Interview
- Lehrer
- Musical education
- Musikpädagogik
- Musikunterricht
- Teacher
- Music lessons
- Qualitative Forschung
- Qualitative research
- Teaching of music
- Object
- Objekt
- Ding
- Handlung
- Practice
- Praxis
- Probationary teacher training
- Referendariat
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
page: 43–55
place: Münster, New York
publication: Soziale Aspekte des Musiklernens
publisher: Waxmann
quality_controlled: '1'
series_title: Musikpädagogische Forschung
status: public
title: Wie kommen die Dinge in den Musikunterricht? Zur Materialität musikpädagogischer
Praxis am Beispiel divergierender Orientierungen im Kontext unterrichtsbezogenen
Handelns angehender Lehrkräfte
type: book_chapter
user_id: '99991'
year: '2018'
...
---
_id: '5633'
abstract:
- lang: eng
text: 'Literature reviews (LRs) are recognized for their increasing impact in the
information systems literature. Methodologists have drawn attention to the question
of how we can leverage the value of LRs to preserve and generate knowledge. The
panelists who participated in the discussion of ?Standalone Literature Reviews
in IS Research: What Can Be Learnt from the Past and Other Fields?? at ICIS 2016
in Dublin acknowledged this significant issue and debated a) what the IS field
can learn from other fields and where IS-specific challenges occur, b) how the
IS field should move forward to foster the genre of LRs, and c) what best practices
are to train doctoral IS students in publishing LRs. This article reports the
key takeaways of this panel discussion. Guidance for IS scholars is provided on
how to conduct LRs that contribute to the cumulative knowledge development within
and across the IS field to best prepare the next generation of IS scholars.'
author:
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
- first_name: Alexander
full_name: Benlian, Alexander
last_name: Benlian
- first_name: Frantz
full_name: Rowe, Frantz
last_name: Rowe
- first_name: Gregor
full_name: Shirley, Gregor
last_name: Shirley
- first_name: Kai
full_name: Larsen, Kai
last_name: Larsen
- first_name: Stacie
full_name: Petter, Stacie
last_name: Petter
- first_name: Guy
full_name: Par{\'e}, Guy
last_name: Par{\'e}
- first_name: Gerit
full_name: Wagner, Gerit
last_name: Wagner
- first_name: Steffi
full_name: Haag, Steffi
last_name: Haag
- first_name: Emrah
full_name: Yasasin, Emrah
last_name: Yasasin
citation:
ama: 'Schryen G, Benlian A, Rowe F, et al. Literature Reviews in IS Research: What
Can Be Learnt from the Past and Other Fields? Communications of the AIS.
2017;40:557-569.'
apa: 'Schryen, G., Benlian, A., Rowe, F., Shirley, G., Larsen, K., Petter, S., …
Yasasin, E. (2017). Literature Reviews in IS Research: What Can Be Learnt from
the Past and Other Fields? Communications of the AIS, 40, 557–569.'
bibtex: '@article{Schryen_Benlian_Rowe_Shirley_Larsen_Petter_Par{\’e}_Wagner_Haag_Yasasin_2017,
title={Literature Reviews in IS Research: What Can Be Learnt from the Past and
Other Fields?}, volume={40}, journal={Communications of the AIS}, publisher={Association
for Information Systems (AIS)}, author={Schryen, Guido and Benlian, Alexander
and Rowe, Frantz and Shirley, Gregor and Larsen, Kai and Petter, Stacie and Par{\’e},
Guy and Wagner, Gerit and Haag, Steffi and Yasasin, Emrah}, year={2017}, pages={557–569}
}'
chicago: 'Schryen, Guido, Alexander Benlian, Frantz Rowe, Gregor Shirley, Kai Larsen,
Stacie Petter, Guy Par{\’e}, Gerit Wagner, Steffi Haag, and Emrah Yasasin. “Literature
Reviews in IS Research: What Can Be Learnt from the Past and Other Fields?” Communications
of the AIS 40 (2017): 557–69.'
ieee: 'G. Schryen et al., “Literature Reviews in IS Research: What Can Be
Learnt from the Past and Other Fields?,” Communications of the AIS, vol.
40, pp. 557–569, 2017.'
mla: 'Schryen, Guido, et al. “Literature Reviews in IS Research: What Can Be Learnt
from the Past and Other Fields?” Communications of the AIS, vol. 40, Association
for Information Systems (AIS), 2017, pp. 557–69.'
short: G. Schryen, A. Benlian, F. Rowe, G. Shirley, K. Larsen, S. Petter, G. Par{\’e},
G. Wagner, S. Haag, E. Yasasin, Communications of the AIS 40 (2017) 557–569.
date_created: 2018-11-14T14:25:40Z
date_updated: 2022-01-06T07:02:14Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
content_type: application/pdf
creator: hsiemes
date_created: 2018-12-07T11:33:59Z
date_updated: 2018-12-13T15:07:15Z
file_id: '6027'
file_name: Schryen et al. (forthcoming), Literature Reviews in IS Research, What
Can Be Learnt from the Past and Other Fields, Communications of th.pdf
file_size: 361850
relation: main_file
file_date_updated: 2018-12-13T15:07:15Z
has_accepted_license: '1'
intvolume: ' 40'
keyword:
- Literature Review
- Review Methodology
- Research Methodology
- Doctoral Training
language:
- iso: eng
oa: '1'
page: 557 - 569
publication: Communications of the AIS
publication_identifier:
issn:
- 1529-3181
publisher: Association for Information Systems (AIS)
status: public
title: 'Literature Reviews in IS Research: What Can Be Learnt from the Past and Other
Fields?'
type: journal_article
user_id: '61579'
volume: 40
year: '2017'
...
---
_id: '10676'
author:
- first_name: Nam
full_name: Ho, Nam
last_name: Ho
- first_name: Paul
full_name: Kaufmann, Paul
last_name: Kaufmann
- first_name: Marco
full_name: Platzner, Marco
id: '398'
last_name: Platzner
citation:
ama: 'Ho N, Kaufmann P, Platzner M. Evolvable caches: Optimization of reconfigurable
cache mappings for a LEON3/Linux-based multi-core processor. In: 2017 International
Conference on Field Programmable Technology (ICFPT). ; 2017:215-218. doi:10.1109/FPT.2017.8280144'
apa: 'Ho, N., Kaufmann, P., & Platzner, M. (2017). Evolvable caches: Optimization
of reconfigurable cache mappings for a LEON3/Linux-based multi-core processor.
In 2017 International Conference on Field Programmable Technology (ICFPT)
(pp. 215–218). https://doi.org/10.1109/FPT.2017.8280144'
bibtex: '@inproceedings{Ho_Kaufmann_Platzner_2017, title={Evolvable caches: Optimization
of reconfigurable cache mappings for a LEON3/Linux-based multi-core processor},
DOI={10.1109/FPT.2017.8280144},
booktitle={2017 International Conference on Field Programmable Technology (ICFPT)},
author={Ho, Nam and Kaufmann, Paul and Platzner, Marco}, year={2017}, pages={215–218}
}'
chicago: 'Ho, Nam, Paul Kaufmann, and Marco Platzner. “Evolvable Caches: Optimization
of Reconfigurable Cache Mappings for a LEON3/Linux-Based Multi-Core Processor.”
In 2017 International Conference on Field Programmable Technology (ICFPT),
215–18, 2017. https://doi.org/10.1109/FPT.2017.8280144.'
ieee: 'N. Ho, P. Kaufmann, and M. Platzner, “Evolvable caches: Optimization of reconfigurable
cache mappings for a LEON3/Linux-based multi-core processor,” in 2017 International
Conference on Field Programmable Technology (ICFPT), 2017, pp. 215–218.'
mla: 'Ho, Nam, et al. “Evolvable Caches: Optimization of Reconfigurable Cache Mappings
for a LEON3/Linux-Based Multi-Core Processor.” 2017 International Conference
on Field Programmable Technology (ICFPT), 2017, pp. 215–18, doi:10.1109/FPT.2017.8280144.'
short: 'N. Ho, P. Kaufmann, M. Platzner, in: 2017 International Conference on Field
Programmable Technology (ICFPT), 2017, pp. 215–218.'
date_created: 2019-07-10T11:22:59Z
date_updated: 2022-01-06T06:50:49Z
department:
- _id: '78'
doi: 10.1109/FPT.2017.8280144
keyword:
- Linux
- cache storage
- microprocessor chips
- multiprocessing systems
- LEON3-Linux based multicore processor
- MiBench suite
- block sizes
- cache adaptation
- evolvable caches
- memory-to-cache-index mapping function
- processor caches
- reconfigurable cache mapping optimization
- reconfigurable hardware technology
- replacement strategies
- standard Linux OS
- time a complete hardware implementation
- Hardware
- Indexes
- Linux
- Measurement
- Multicore processing
- Optimization
- Training
language:
- iso: eng
page: 215-218
publication: 2017 International Conference on Field Programmable Technology (ICFPT)
status: public
title: 'Evolvable caches: Optimization of reconfigurable cache mappings for a LEON3/Linux-based
multi-core processor'
type: conference
user_id: '398'
year: '2017'
...
---
_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: '11867'
abstract:
- lang: eng
text: 'New waves of consumer-centric applications, such as voice search and voice
interaction with mobile devices and home entertainment systems, increasingly require
automatic speech recognition (ASR) to be robust to the full range of real-world
noise and other acoustic distorting conditions. Despite its practical importance,
however, the inherent links between and distinctions among the myriad of methods
for noise-robust ASR have yet to be carefully studied in order to advance the
field further. To this end, it is critical to establish a solid, consistent, and
common mathematical foundation for noise-robust ASR, which is lacking at present.
This article is intended to fill this gap and to provide a thorough overview of
modern noise-robust techniques for ASR developed over the past 30 years. We emphasize
methods that are proven to be successful and that are likely to sustain or expand
their future applicability. We distill key insights from our comprehensive overview
in this field and take a fresh look at a few old problems, which nevertheless
are still highly relevant today. Specifically, we have analyzed and categorized
a wide range of noise-robust techniques using five different criteria: 1) feature-domain
vs. model-domain processing, 2) the use of prior knowledge about the acoustic
environment distortion, 3) the use of explicit environment-distortion models,
4) deterministic vs. uncertainty processing, and 5) the use of acoustic models
trained jointly with the same feature enhancement or model adaptation process
used in the testing stage. With this taxonomy-oriented review, we equip the reader
with the insight to choose among techniques and with the awareness of the performance-complexity
tradeoffs. The pros and cons of using different noise-robust ASR techniques in
practical application scenarios are provided as a guide to interested practitioners.
The current challenges and future research directions in this field is also carefully
analyzed.'
author:
- first_name: Jinyu
full_name: Li, Jinyu
last_name: Li
- first_name: Li
full_name: Deng, Li
last_name: Deng
- first_name: Yifan
full_name: Gong, Yifan
last_name: Gong
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Li J, Deng L, Gong Y, Haeb-Umbach R. An Overview of Noise-Robust Automatic
Speech Recognition. IEEE Transactions on Audio, Speech and Language Processing.
2014;22(4):745-777. doi:10.1109/TASLP.2014.2304637
apa: Li, J., Deng, L., Gong, Y., & Haeb-Umbach, R. (2014). An Overview of Noise-Robust
Automatic Speech Recognition. IEEE Transactions on Audio, Speech and Language
Processing, 22(4), 745–777. https://doi.org/10.1109/TASLP.2014.2304637
bibtex: '@article{Li_Deng_Gong_Haeb-Umbach_2014, title={An Overview of Noise-Robust
Automatic Speech Recognition}, volume={22}, DOI={10.1109/TASLP.2014.2304637},
number={4}, journal={IEEE Transactions on Audio, Speech and Language Processing},
author={Li, Jinyu and Deng, Li and Gong, Yifan and Haeb-Umbach, Reinhold}, year={2014},
pages={745–777} }'
chicago: 'Li, Jinyu, Li Deng, Yifan Gong, and Reinhold Haeb-Umbach. “An Overview
of Noise-Robust Automatic Speech Recognition.” IEEE Transactions on Audio,
Speech and Language Processing 22, no. 4 (2014): 745–77. https://doi.org/10.1109/TASLP.2014.2304637.'
ieee: J. Li, L. Deng, Y. Gong, and R. Haeb-Umbach, “An Overview of Noise-Robust
Automatic Speech Recognition,” IEEE Transactions on Audio, Speech and Language
Processing, vol. 22, no. 4, pp. 745–777, 2014.
mla: Li, Jinyu, et al. “An Overview of Noise-Robust Automatic Speech Recognition.”
IEEE Transactions on Audio, Speech and Language Processing, vol. 22, no.
4, 2014, pp. 745–77, doi:10.1109/TASLP.2014.2304637.
short: J. Li, L. Deng, Y. Gong, R. Haeb-Umbach, IEEE Transactions on Audio, Speech
and Language Processing 22 (2014) 745–777.
date_created: 2019-07-12T05:29:47Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASLP.2014.2304637
intvolume: ' 22'
issue: '4'
keyword:
- Speech recognition
- compensation
- distortion modeling
- joint model training
- noise
- robustness
- uncertainty processing
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6732927
oa: '1'
page: 745-777
publication: IEEE Transactions on Audio, Speech and Language Processing
status: public
title: An Overview of Noise-Robust Automatic Speech Recognition
type: journal_article
user_id: '44006'
volume: 22
year: '2014'
...
---
_id: '11816'
abstract:
- lang: eng
text: In this paper, we consider the Maximum Likelihood (ML) estimation of the parameters
of a GAUSSIAN in the presence of censored, i.e., clipped data. We show that the
resulting Expectation Maximization (EM) algorithm delivers virtually biasfree
and efficient estimates, and we discuss its convergence properties. We also discuss
optimal classification in the presence of censored data. Censored data are frequently
encountered in wireless LAN positioning systems based on the fingerprinting method
employing signal strength measurements, due to the limited sensitivity of the
portable devices. Experiments both on simulated and real-world data demonstrate
the effectiveness of the proposed algorithms.
author:
- first_name: Manh Kha
full_name: Hoang, Manh Kha
last_name: Hoang
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Hoang MK, Haeb-Umbach R. Parameter estimation and classification of censored
Gaussian data with application to WiFi indoor positioning. In: 38th International
Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013). ; 2013:3721-3725.
doi:10.1109/ICASSP.2013.6638353'
apa: Hoang, M. K., & Haeb-Umbach, R. (2013). Parameter estimation and classification
of censored Gaussian data with application to WiFi indoor positioning. In 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)
(pp. 3721–3725). https://doi.org/10.1109/ICASSP.2013.6638353
bibtex: '@inproceedings{Hoang_Haeb-Umbach_2013, title={Parameter estimation and
classification of censored Gaussian data with application to WiFi indoor positioning},
DOI={10.1109/ICASSP.2013.6638353},
booktitle={38th International Conference on Acoustics, Speech, and Signal Processing
(ICASSP 2013)}, author={Hoang, Manh Kha and Haeb-Umbach, Reinhold}, year={2013},
pages={3721–3725} }'
chicago: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
of Censored Gaussian Data with Application to WiFi Indoor Positioning.” In 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
3721–25, 2013. https://doi.org/10.1109/ICASSP.2013.6638353.
ieee: M. K. Hoang and R. Haeb-Umbach, “Parameter estimation and classification of
censored Gaussian data with application to WiFi indoor positioning,” in 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
2013, pp. 3721–3725.
mla: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
of Censored Gaussian Data with Application to WiFi Indoor Positioning.” 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
2013, pp. 3721–25, doi:10.1109/ICASSP.2013.6638353.
short: 'M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.'
date_created: 2019-07-12T05:28:48Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638353
keyword:
- Gaussian processes
- Global Positioning System
- convergence
- expectation-maximisation algorithm
- fingerprint identification
- indoor radio
- signal classification
- wireless LAN
- EM algorithm
- ML estimation
- WiFi indoor positioning
- censored Gaussian data classification
- clipped data
- convergence properties
- expectation maximization algorithm
- fingerprinting method
- maximum likelihood estimation
- optimal classification
- parameters estimation
- portable devices sensitivity
- signal strength measurements
- wireless LAN positioning systems
- Convergence
- IEEE 802.11 Standards
- Maximum likelihood estimation
- Parameter estimation
- Position measurement
- Training
- Indoor positioning
- censored data
- expectation maximization
- signal strength
- wireless LAN
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013.pdf
oa: '1'
page: 3721-3725
publication: 38th International Conference on Acoustics, Speech, and Signal Processing
(ICASSP 2013)
publication_identifier:
issn:
- 1520-6149
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013_Poster.pdf
status: public
title: Parameter estimation and classification of censored Gaussian data with application
to WiFi indoor positioning
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11938'
abstract:
- lang: eng
text: In this paper, parameter estimation of a state-space model of noise or noisy
speech cepstra is investigated. A blockwise EM algorithm is derived for the estimation
of the state and observation noise covariance from noise-only input data. It is
supposed to be used during the offline training mode of a speech recognizer. Further
a sequential online EM algorithm is developed to adapt the observation noise covariance
on noisy speech cepstra at its input. The estimated parameters are then used in
model-based speech feature enhancement for noise-robust automatic speech recognition.
Experiments on the AURORA4 database lead to improved recognition results with
a linear state model compared to the assumption of stationary noise.
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. Parameter Estimation of a State-Space Model of Noise
for Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language
Processing. 2009;17(8):1577-1590. doi:10.1109/TASL.2009.2023172
apa: Windmann, S., & Haeb-Umbach, R. (2009). Parameter Estimation of a State-Space
Model of Noise for Robust Speech Recognition. IEEE Transactions on Audio, Speech,
and Language Processing, 17(8), 1577–1590. https://doi.org/10.1109/TASL.2009.2023172
bibtex: '@article{Windmann_Haeb-Umbach_2009, title={Parameter Estimation of a State-Space
Model of Noise for Robust Speech Recognition}, volume={17}, DOI={10.1109/TASL.2009.2023172},
number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={1577–1590}
}'
chicago: 'Windmann, Stefan, and Reinhold Haeb-Umbach. “Parameter Estimation of a
State-Space Model of Noise for Robust Speech Recognition.” IEEE Transactions
on Audio, Speech, and Language Processing 17, no. 8 (2009): 1577–90. https://doi.org/10.1109/TASL.2009.2023172.'
ieee: S. Windmann and R. Haeb-Umbach, “Parameter Estimation of a State-Space Model
of Noise for Robust Speech Recognition,” IEEE Transactions on Audio, Speech,
and Language Processing, vol. 17, no. 8, pp. 1577–1590, 2009.
mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Parameter Estimation of a State-Space
Model of Noise for Robust Speech Recognition.” IEEE Transactions on Audio,
Speech, and Language Processing, vol. 17, no. 8, 2009, pp. 1577–90, doi:10.1109/TASL.2009.2023172.
short: S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 17 (2009) 1577–1590.
date_created: 2019-07-12T05:31:09Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/TASL.2009.2023172
intvolume: ' 17'
issue: '8'
keyword:
- AURORA4 database
- blockwise EM algorithm
- covariance analysis
- linear state model
- noise covariance
- noise-robust automatic speech recognition
- noisy speech cepstra
- offline training mode
- parameter estimation
- speech recognition
- speech recognition equipment
- speech recognizer
- state-space methods
- state-space model
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-2.pdf
oa: '1'
page: 1577-1590
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition
type: journal_article
user_id: '44006'
volume: 17
year: '2009'
...
---
_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'
...
---
_id: '11778'
abstract:
- lang: eng
text: In this paper, it is shown that a correlation criterion is the appropriate
criterion for bottom-up clustering to obtain broad phonetic class regression trees
for maximum likelihood linear regression (MLLR)-based speaker adaptation. The
correlation structure among speech units is estimated on the speaker-independent
training data. In adaptation experiments the tree outperformed a regression tree
obtained from clustering according to closeness in acoustic space and achieved
results comparable with those of a manually designed broad phonetic class tree
author:
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Haeb-Umbach R. Automatic generation of phonetic regression class trees for
MLLR adaptation. IEEE Transactions on Speech and Audio Processing. 2001;9(3):299-302.
doi:10.1109/89.906003
apa: Haeb-Umbach, R. (2001). Automatic generation of phonetic regression class trees
for MLLR adaptation. IEEE Transactions on Speech and Audio Processing,
9(3), 299–302. https://doi.org/10.1109/89.906003
bibtex: '@article{Haeb-Umbach_2001, title={Automatic generation of phonetic regression
class trees for MLLR adaptation}, volume={9}, DOI={10.1109/89.906003},
number={3}, journal={IEEE Transactions on Speech and Audio Processing}, author={Haeb-Umbach,
Reinhold}, year={2001}, pages={299–302} }'
chicago: 'Haeb-Umbach, Reinhold. “Automatic Generation of Phonetic Regression Class
Trees for MLLR Adaptation.” IEEE Transactions on Speech and Audio Processing
9, no. 3 (2001): 299–302. https://doi.org/10.1109/89.906003.'
ieee: R. Haeb-Umbach, “Automatic generation of phonetic regression class trees for
MLLR adaptation,” IEEE Transactions on Speech and Audio Processing, vol.
9, no. 3, pp. 299–302, 2001.
mla: Haeb-Umbach, Reinhold. “Automatic Generation of Phonetic Regression Class Trees
for MLLR Adaptation.” IEEE Transactions on Speech and Audio Processing,
vol. 9, no. 3, 2001, pp. 299–302, doi:10.1109/89.906003.
short: R. Haeb-Umbach, IEEE Transactions on Speech and Audio Processing 9 (2001)
299–302.
date_created: 2019-07-12T05:28:04Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
doi: 10.1109/89.906003
intvolume: ' 9'
issue: '3'
keyword:
- acoustic space
- adaptation experiments
- automatic generation
- bottom-up clustering
- broad phonetic class regression trees
- correlation criterion
- correlation methods
- maximum likelihood estimation
- maximum likelihood linear regression based speaker adaptation
- MLLR adaptation
- pattern clustering
- phonetic regression class trees
- speaker-independent training data
- speech recognition
- speech units
- statistical analysis
- trees (mathematics)
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2001/Ha01.pdf
oa: '1'
page: 299-302
publication: IEEE Transactions on Speech and Audio Processing
status: public
title: Automatic generation of phonetic regression class trees for MLLR adaptation
type: journal_article
user_id: '44006'
volume: 9
year: '2001'
...