---
_id: '11740'
abstract:
- lang: eng
text: In this contribution we derive the Maximum A-Posteriori (MAP) estimates of
the parameters of a Gaussian Mixture Model (GMM) in the presence of noisy observations.
We assume the distortion to be white Gaussian noise of known mean and variance.
An approximate conjugate prior of the GMM parameters is derived allowing for a
computationally efficient implementation in a sequential estimation framework.
Simulations on artificially generated data demonstrate the superiority of the
proposed method compared to the Maximum Likelihood technique and to the ordinary
MAP approach, whose estimates are corrected by the known statistics of the distortion
in a straightforward manner.
author:
- first_name: Aleksej
full_name: Chinaev, Aleksej
last_name: Chinaev
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Chinaev A, Haeb-Umbach R. MAP-based Estimation of the Parameters of a Gaussian
Mixture Model in the Presence of Noisy Observations. In: 38th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). ; 2013:3352-3356.
doi:10.1109/ICASSP.2013.6638279'
apa: Chinaev, A., & Haeb-Umbach, R. (2013). MAP-based Estimation of the Parameters
of a Gaussian Mixture Model in the Presence of Noisy Observations. In 38th
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)
(pp. 3352–3356). https://doi.org/10.1109/ICASSP.2013.6638279
bibtex: '@inproceedings{Chinaev_Haeb-Umbach_2013, title={MAP-based Estimation of
the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations},
DOI={10.1109/ICASSP.2013.6638279},
booktitle={38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013)}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2013},
pages={3352–3356} }'
chicago: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the
Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.”
In 38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013), 3352–56, 2013. https://doi.org/10.1109/ICASSP.2013.6638279.
ieee: A. Chinaev and R. Haeb-Umbach, “MAP-based Estimation of the Parameters of
a Gaussian Mixture Model in the Presence of Noisy Observations,” in 38th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013,
pp. 3352–3356.
mla: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters
of a Gaussian Mixture Model in the Presence of Noisy Observations.” 38th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013,
pp. 3352–56, doi:10.1109/ICASSP.2013.6638279.
short: 'A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.'
date_created: 2019-07-12T05:27:20Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638279
keyword:
- Gaussian noise
- maximum likelihood estimation
- parameter estimation
- GMM parameter
- Gaussian mixture model
- MAP estimation
- Map-based estimation
- maximum a-posteriori estimation
- maximum likelihood technique
- noisy observation
- sequential estimation framework
- white Gaussian noise
- Additive noise
- Gaussian mixture model
- Maximum likelihood estimation
- Noise measurement
- Gaussian mixture model
- Maximum a posteriori estimation
- Maximum likelihood estimation
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13.pdf
oa: '1'
page: 3352-3356
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/ChHa13_Poster.pdf
status: public
title: MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence
of Noisy Observations
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11862'
abstract:
- lang: eng
text: In this contribution we extend a previously proposed Bayesian approach for
the enhancement of reverberant logarithmic mel power spectral coefficients for
robust automatic speech recognition to the additional compensation of background
noise. A recently proposed observation model is employed whose time-variant observation
error statistics are obtained as a side product of the inference of the a posteriori
probability density function of the clean speech feature vectors. Further a reduction
of the computational effort and the memory requirements are achieved by using
a recursive formulation of the observation model. The performance of the proposed
algorithms is first experimentally studied on a connected digits recognition task
with artificially created noisy reverberant data. It is shown that the use of
the time-variant observation error model leads to a significant error rate reduction
at low signal-to-noise ratios compared to a time-invariant model. Further experiments
were conducted on a 5000 word task recorded in a reverberant and noisy environment.
A significant word error rate reduction was obtained demonstrating the effectiveness
of the approach on real-world data.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Leutnant V, Krueger A, Haeb-Umbach R. Bayesian Feature Enhancement for Reverberation
and Noise Robust Speech Recognition. IEEE Transactions on Audio, Speech, and
Language Processing. 2013;21(8):1640-1652. doi:10.1109/TASL.2013.2258013
apa: Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2013). Bayesian Feature Enhancement
for Reverberation and Noise Robust Speech Recognition. IEEE Transactions on
Audio, Speech, and Language Processing, 21(8), 1640–1652. https://doi.org/10.1109/TASL.2013.2258013
bibtex: '@article{Leutnant_Krueger_Haeb-Umbach_2013, title={Bayesian Feature Enhancement
for Reverberation and Noise Robust Speech Recognition}, volume={21}, DOI={10.1109/TASL.2013.2258013},
number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2013},
pages={1640–1652} }'
chicago: 'Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “Bayesian
Feature Enhancement for Reverberation and Noise Robust Speech Recognition.” IEEE
Transactions on Audio, Speech, and Language Processing 21, no. 8 (2013): 1640–52.
https://doi.org/10.1109/TASL.2013.2258013.'
ieee: V. Leutnant, A. Krueger, and R. Haeb-Umbach, “Bayesian Feature Enhancement
for Reverberation and Noise Robust Speech Recognition,” IEEE Transactions on
Audio, Speech, and Language Processing, vol. 21, no. 8, pp. 1640–1652, 2013.
mla: Leutnant, Volker, et al. “Bayesian Feature Enhancement for Reverberation and
Noise Robust Speech Recognition.” IEEE Transactions on Audio, Speech, and Language
Processing, vol. 21, no. 8, 2013, pp. 1640–52, doi:10.1109/TASL.2013.2258013.
short: V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech,
and Language Processing 21 (2013) 1640–1652.
date_created: 2019-07-12T05:29:42Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2013.2258013
intvolume: ' 21'
issue: '8'
keyword:
- Bayes methods
- compensation
- error statistics
- reverberation
- speech recognition
- Bayesian feature enhancement
- background noise
- clean speech feature vectors
- compensation
- connected digits recognition task
- error statistics
- memory requirements
- noisy reverberant data
- posteriori probability density function
- recursive formulation
- reverberant logarithmic mel power spectral coefficients
- robust automatic speech recognition
- signal-to-noise ratios
- time-variant observation
- word error rate reduction
- Robust automatic speech recognition
- model-based Bayesian feature enhancement
- observation model for reverberant and noisy speech
- recursive observation model
language:
- iso: eng
page: 1640-1652
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition
type: journal_article
user_id: '44006'
volume: 21
year: '2013'
...
---
_id: '11917'
abstract:
- lang: eng
text: In this paper we present a speech presence probability (SPP) estimation algorithmwhich
exploits both temporal and spectral correlations of speech. To this end, the SPP
estimation is formulated as the posterior probability estimation of the states
of a two-dimensional (2D) Hidden Markov Model (HMM). We derive an iterative algorithm
to decode the 2D-HMM which is based on the turbo principle. The experimental results
show that indeed the SPP estimates improve from iteration to iteration, and further
clearly outperform another state-of-the-art SPP estimation algorithm.
author:
- first_name: Dang Hai Tran
full_name: Vu, Dang Hai Tran
last_name: Vu
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Vu DHT, Haeb-Umbach R. Using the turbo principle for exploiting temporal and
spectral correlations in speech presence probability estimation. In: 38th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). ; 2013:863-867.
doi:10.1109/ICASSP.2013.6637771'
apa: Vu, D. H. T., & Haeb-Umbach, R. (2013). Using the turbo principle for exploiting
temporal and spectral correlations in speech presence probability estimation.
In 38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013) (pp. 863–867). https://doi.org/10.1109/ICASSP.2013.6637771
bibtex: '@inproceedings{Vu_Haeb-Umbach_2013, title={Using the turbo principle for
exploiting temporal and spectral correlations in speech presence probability estimation},
DOI={10.1109/ICASSP.2013.6637771},
booktitle={38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013)}, author={Vu, Dang Hai Tran and Haeb-Umbach, Reinhold}, year={2013},
pages={863–867} }'
chicago: Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle
for Exploiting Temporal and Spectral Correlations in Speech Presence Probability
Estimation.” In 38th International Conference on Acoustics, Speech and Signal
Processing (ICASSP 2013), 863–67, 2013. https://doi.org/10.1109/ICASSP.2013.6637771.
ieee: D. H. T. Vu and R. Haeb-Umbach, “Using the turbo principle for exploiting
temporal and spectral correlations in speech presence probability estimation,”
in 38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013), 2013, pp. 863–867.
mla: Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle for
Exploiting Temporal and Spectral Correlations in Speech Presence Probability Estimation.”
38th International Conference on Acoustics, Speech and Signal Processing (ICASSP
2013), 2013, pp. 863–67, doi:10.1109/ICASSP.2013.6637771.
short: 'D.H.T. Vu, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.'
date_created: 2019-07-12T05:30:45Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6637771
keyword:
- correlation methods
- estimation theory
- hidden Markov models
- iterative methods
- probability
- spectral analysis
- speech processing
- 2D HMM
- SPP estimates
- iterative algorithm
- posterior probability estimation
- spectral correlation
- speech presence probability estimation
- state-of-the-art SPP estimation algorithm
- temporal correlation
- turbo principle
- two-dimensional hidden Markov model
- Correlation
- Decoding
- Estimation
- Iterative decoding
- Noise
- Speech
- Vectors
language:
- iso: eng
page: 863-867
publication: 38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013)
publication_identifier:
issn:
- 1520-6149
status: public
title: Using the turbo principle for exploiting temporal and spectral correlations
in speech presence probability estimation
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11818'
abstract:
- lang: eng
text: In this paper we present a system for indoor navigation based on received
signal strength index information of Wireless-LAN access points and relative position
estimates. The relative position information is gathered from inertial smartphone
sensors using a step detection and an orientation estimate. Our map data is hosted
on a server employing a map renderer and a SQL database. The database includes
a complete multilevel office building, within which the user can navigate. During
navigation, the client retrieves the position estimate from the server, together
with the corresponding map tiles to visualize the user's position on the smartphone
display.
author:
- first_name: Manh Kha
full_name: Hoang, Manh Kha
last_name: Hoang
- first_name: Sarah
full_name: Schmitz, Sarah
last_name: Schmitz
- first_name: Christian
full_name: Drueke, Christian
last_name: Drueke
- first_name: Dang Hai Tran
full_name: Vu, Dang Hai Tran
last_name: Vu
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Hoang MK, Schmitz S, Drueke C, Vu DHT, Schmalenstroeer J, Haeb-Umbach R. Server
based indoor navigation using RSSI and inertial sensor information. In: Positioning
Navigation and Communication (WPNC), 2013 10th Workshop On. ; 2013:1-6. doi:10.1109/WPNC.2013.6533263'
apa: Hoang, M. K., Schmitz, S., Drueke, C., Vu, D. H. T., Schmalenstroeer, J., &
Haeb-Umbach, R. (2013). Server based indoor navigation using RSSI and inertial
sensor information. Positioning Navigation and Communication (WPNC), 2013 10th
Workshop On, 1–6. https://doi.org/10.1109/WPNC.2013.6533263
bibtex: '@inproceedings{Hoang_Schmitz_Drueke_Vu_Schmalenstroeer_Haeb-Umbach_2013,
title={Server based indoor navigation using RSSI and inertial sensor information},
DOI={10.1109/WPNC.2013.6533263},
booktitle={Positioning Navigation and Communication (WPNC), 2013 10th Workshop
on}, author={Hoang, Manh Kha and Schmitz, Sarah and Drueke, Christian and Vu,
Dang Hai Tran and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2013},
pages={1–6} }'
chicago: Hoang, Manh Kha, Sarah Schmitz, Christian Drueke, Dang Hai Tran Vu, Joerg
Schmalenstroeer, and Reinhold Haeb-Umbach. “Server Based Indoor Navigation Using
RSSI and Inertial Sensor Information.” In Positioning Navigation and Communication
(WPNC), 2013 10th Workshop On, 1–6, 2013. https://doi.org/10.1109/WPNC.2013.6533263.
ieee: 'M. K. Hoang, S. Schmitz, C. Drueke, D. H. T. Vu, J. Schmalenstroeer, and
R. Haeb-Umbach, “Server based indoor navigation using RSSI and inertial sensor
information,” in Positioning Navigation and Communication (WPNC), 2013 10th
Workshop on, 2013, pp. 1–6, doi: 10.1109/WPNC.2013.6533263.'
mla: Hoang, Manh Kha, et al. “Server Based Indoor Navigation Using RSSI and Inertial
Sensor Information.” Positioning Navigation and Communication (WPNC), 2013
10th Workshop On, 2013, pp. 1–6, doi:10.1109/WPNC.2013.6533263.
short: 'M.K. Hoang, S. Schmitz, C. Drueke, D.H.T. Vu, J. Schmalenstroeer, R. Haeb-Umbach,
in: Positioning Navigation and Communication (WPNC), 2013 10th Workshop On, 2013,
pp. 1–6.'
date_created: 2019-07-12T05:28:51Z
date_updated: 2023-10-26T08:09:36Z
department:
- _id: '54'
doi: 10.1109/WPNC.2013.6533263
keyword:
- SQL
- navigation
- smart phones
- wireless LAN
- RSSI
- SQL database
- complete multilevel office building
- inertial sensor information
- inertial smartphone sensors
- map renderer
- received signal strength index information
- relative position estimates
- server based indoor navigation
- step detection
- wireless-LAN access points
- Smartphone
- fingerprint
- indoor navigation
- map tile
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrScHa2013.pdf
oa: '1'
page: 1-6
publication: Positioning Navigation and Communication (WPNC), 2013 10th Workshop on
quality_controlled: '1'
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrScHa2013_Poster.pdf
status: public
title: Server based indoor navigation using RSSI and inertial sensor information
type: conference
user_id: '460'
year: '2013'
...
---
_id: '5192'
abstract:
- lang: eng
text: For the valuation of fast growing innovative firms Schwartz and Moon (Financ
Anal J 56:62–75, 2000), (Financ Rev 36:7–26, 2001) develop a fundamental valuation
model where key parameters follow stochastic processes. While prior research shows
promising potential for this model, it has never been tested on a large scale
dataset. Thus, guided by economic theory, this paper is the first to design a
large-scale applicable implementation on around 30,000 technology firm quarter
observations from 1992 to 2009 for the US to assess this model. Evaluating the
feasibility and performance of the Schwartz-Moon model reveals that it is comparably
accurate to the traditional sales multiple with key advantages in valuing small
and non-listed firms. Most importantly, however, the model is able to indicate
severe market over- or undervaluation from a fundamental perspective. We demonstrate
that a trading strategy based on our implementation has significant investment
value. Consequently, the model seems suitable for detecting misvaluations as the
dot-com bubble.
article_type: original
author:
- first_name: Jan
full_name: Klobucnik, Jan
last_name: Klobucnik
- first_name: Sönke
full_name: Sievers, Sönke
id: '46447'
last_name: Sievers
citation:
ama: Klobucnik J, Sievers S. Valuing high technology growth firms. Journal of
Business Economics (VHB-JOURQUAL 4 Ranking B). 2013;83(9):947-984. doi:https://doi.org/10.1007/s11573-013-0684-2
apa: Klobucnik, J., & Sievers, S. (2013). Valuing high technology growth firms.
Journal of Business Economics (VHB-JOURQUAL 4 Ranking B), 83(9),
947–984. https://doi.org/10.1007/s11573-013-0684-2
bibtex: '@article{Klobucnik_Sievers_2013, title={Valuing high technology growth
firms}, volume={83}, DOI={https://doi.org/10.1007/s11573-013-0684-2},
number={9}, journal={Journal of Business Economics (VHB-JOURQUAL 4 Ranking B)},
publisher={Springer}, author={Klobucnik, Jan and Sievers, Sönke}, year={2013},
pages={947–984} }'
chicago: 'Klobucnik, Jan, and Sönke Sievers. “Valuing High Technology Growth Firms.”
Journal of Business Economics (VHB-JOURQUAL 4 Ranking B) 83, no. 9 (2013):
947–84. https://doi.org/10.1007/s11573-013-0684-2.'
ieee: 'J. Klobucnik and S. Sievers, “Valuing high technology growth firms,” Journal
of Business Economics (VHB-JOURQUAL 4 Ranking B), vol. 83, no. 9, pp. 947–984,
2013, doi: https://doi.org/10.1007/s11573-013-0684-2.'
mla: Klobucnik, Jan, and Sönke Sievers. “Valuing High Technology Growth Firms.”
Journal of Business Economics (VHB-JOURQUAL 4 Ranking B), vol. 83, no.
9, Springer, 2013, pp. 947–84, doi:https://doi.org/10.1007/s11573-013-0684-2.
short: J. Klobucnik, S. Sievers, Journal of Business Economics (VHB-JOURQUAL 4 Ranking
B) 83 (2013) 947–984.
date_created: 2018-10-31T11:31:56Z
date_updated: 2026-04-09T08:00:16Z
department:
- _id: '275'
doi: https://doi.org/10.1007/s11573-013-0684-2
extern: '1'
intvolume: ' 83'
issue: '9'
jel:
- G11
- G12
- G17
- G33
keyword:
- Schwartz-Moon model
- Market mispricing
- Empirical test
- Company valuation
- Trading strategy
language:
- iso: eng
main_file_link:
- url: https://link.springer.com/article/10.1007/s11573-013-0684-2
page: 947-984
publication: Journal of Business Economics (VHB-JOURQUAL 4 Ranking B)
publication_status: published
publisher: Springer
quality_controlled: '1'
status: public
title: Valuing high technology growth firms
type: journal_article
user_id: '115848'
volume: 83
year: '2013'
...
---
_id: '5113'
abstract:
- lang: eng
text: 'Standard equity valuation approaches (i.e., DDM, RIM, and DCF model) are
derived under the assumption of ideal conditions, such as infinite payoffs and
clean surplus accounting. Because these conditions are hardly ever met, we extend
the standard approaches, based on the fundamental principle of financial statement
articulation. The extended models are then tested empirically by employing two
sets of forecasts: (1) analyst forecasts provided by Value Line and (2) forecasts
generated by cross-sectional regression models. The main result is that our extended
models yield considerably smaller valuation errors. Moreover, by construction,
identical value estimates are obtained across the extended models. By reestablishing
empirical equivalence under non-ideal conditions, our approach provides a benchmark
that enables us to quantify the errors resulting from individual deviations from
ideal conditions, and thus, to analyze the robustness of the standard approaches.
Finally, by providing a level playing field for the different valuation approaches,
our findings have implications for other empirical settings, for example, estimating
the implied cost of capital. '
article_type: original
author:
- first_name: Nicolas
full_name: Heinrichs, Nicolas
last_name: Heinrichs
- first_name: Dieter
full_name: Hess, Dieter
last_name: Hess
- first_name: Carsten
full_name: Homburg, Carsten
last_name: Homburg
- first_name: Michael
full_name: Lorenz, Michael
last_name: Lorenz
- first_name: Sönke
full_name: Sievers, Sönke
id: '46447'
last_name: Sievers
citation:
ama: 'Heinrichs N, Hess D, Homburg C, Lorenz M, Sievers S. Extended dividend, cash
flow, and residual income valuation models: Accounting for deviations from ideal
conditions. Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+).
2013;30(1):42-79. doi:10.2139/ssrn.1145201'
apa: 'Heinrichs, N., Hess, D., Homburg, C., Lorenz, M., & Sievers, S. (2013).
Extended dividend, cash flow, and residual income valuation models: Accounting
for deviations from ideal conditions. Contemporary Accounting Research (VHB-JOURQUAL
4 Ranking A+), 30(1), 42–79. https://doi.org/10.2139/ssrn.1145201'
bibtex: '@article{Heinrichs_Hess_Homburg_Lorenz_Sievers_2013, title={Extended dividend,
cash flow, and residual income valuation models: Accounting for deviations from
ideal conditions}, volume={30}, DOI={10.2139/ssrn.1145201},
number={1}, journal={Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking
A+)}, publisher={Wiley Online Library}, author={Heinrichs, Nicolas and Hess, Dieter
and Homburg, Carsten and Lorenz, Michael and Sievers, Sönke}, year={2013}, pages={42–79}
}'
chicago: 'Heinrichs, Nicolas, Dieter Hess, Carsten Homburg, Michael Lorenz, and
Sönke Sievers. “Extended Dividend, Cash Flow, and Residual Income Valuation Models:
Accounting for Deviations from Ideal Conditions.” Contemporary Accounting Research
(VHB-JOURQUAL 4 Ranking A+) 30, no. 1 (2013): 42–79. https://doi.org/10.2139/ssrn.1145201.'
ieee: 'N. Heinrichs, D. Hess, C. Homburg, M. Lorenz, and S. Sievers, “Extended dividend,
cash flow, and residual income valuation models: Accounting for deviations from
ideal conditions,” Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking
A+), vol. 30, no. 1, pp. 42–79, 2013, doi: 10.2139/ssrn.1145201.'
mla: 'Heinrichs, Nicolas, et al. “Extended Dividend, Cash Flow, and Residual Income
Valuation Models: Accounting for Deviations from Ideal Conditions.” Contemporary
Accounting Research (VHB-JOURQUAL 4 Ranking A+), vol. 30, no. 1, Wiley Online
Library, 2013, pp. 42–79, doi:10.2139/ssrn.1145201.'
short: N. Heinrichs, D. Hess, C. Homburg, M. Lorenz, S. Sievers, Contemporary Accounting
Research (VHB-JOURQUAL 4 Ranking A+) 30 (2013) 42–79.
date_created: 2018-10-31T07:58:17Z
date_updated: 2026-04-09T08:22:32Z
department:
- _id: '275'
doi: 10.2139/ssrn.1145201
extern: '1'
intvolume: ' 30'
issue: '1'
jel:
- G12
- G14
- M41
keyword:
- Dividend Discount Model
- Residual Income
- Discounted Cash Flow
- Dirty Surplus
- Terminal Value
- Valuation Error
language:
- iso: eng
main_file_link:
- url: http://onlinelibrary.wiley.com/doi/10.1111/j.1911-3846.2011.01148.x/abstract
page: 42-79
publication: Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+)
publication_status: published
publisher: Wiley Online Library
quality_controlled: '1'
related_material:
link:
- relation: earlier_version
url: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1145201
status: public
title: 'Extended dividend, cash flow, and residual income valuation models: Accounting
for deviations from ideal conditions'
type: journal_article
user_id: '115848'
volume: 30
year: '2013'
...
---
_id: '22737'
author:
- first_name: Matthias
full_name: Becker, Matthias
last_name: Becker
- first_name: Markus
full_name: Luckey, Markus
last_name: Luckey
- first_name: Steffen
full_name: Becker, Steffen
last_name: Becker
citation:
ama: 'Becker M, Luckey M, Becker S. Model-driven Performance Engineering of Self-adaptive
Systems: A Survey. In: {Proceedings of the 8th International ACM SIGSOFT Conference
on Quality of Software Architectures (QoSA)}. New York, NY, USA: ACM; 2012:117-122.
doi:10.1145/2304696.2304716'
apa: 'Becker, M., Luckey, M., & Becker, S. (2012). Model-driven Performance
Engineering of Self-adaptive Systems: A Survey. In {Proceedings of the 8th
International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}
(pp. 117–122). New York, NY, USA: ACM. https://doi.org/10.1145/2304696.2304716'
bibtex: '@inproceedings{Becker_Luckey_Becker_2012, place={New York, NY, USA}, title={Model-driven
Performance Engineering of Self-adaptive Systems: A Survey}, DOI={10.1145/2304696.2304716},
booktitle={{Proceedings of the 8th International ACM SIGSOFT Conference on Quality
of Software Architectures (QoSA)}}, publisher={ACM}, author={Becker, Matthias
and Luckey, Markus and Becker, Steffen}, year={2012}, pages={117–122} }'
chicago: 'Becker, Matthias, Markus Luckey, and Steffen Becker. “Model-Driven Performance
Engineering of Self-Adaptive Systems: A Survey.” In {Proceedings of the 8th
International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)},
117–22. New York, NY, USA: ACM, 2012. https://doi.org/10.1145/2304696.2304716.'
ieee: 'M. Becker, M. Luckey, and S. Becker, “Model-driven Performance Engineering
of Self-adaptive Systems: A Survey,” in {Proceedings of the 8th International
ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}, 2012,
pp. 117–122.'
mla: 'Becker, Matthias, et al. “Model-Driven Performance Engineering of Self-Adaptive
Systems: A Survey.” {Proceedings of the 8th International ACM SIGSOFT Conference
on Quality of Software Architectures (QoSA)}, ACM, 2012, pp. 117–22, doi:10.1145/2304696.2304716.'
short: 'M. Becker, M. Luckey, S. Becker, in: {Proceedings of the 8th International
ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}, ACM, New
York, NY, USA, 2012, pp. 117–122.'
date_created: 2021-07-15T08:38:08Z
date_updated: 2022-01-06T06:55:39Z
doi: 10.1145/2304696.2304716
keyword:
- model-driven performance engineering
- self-*
- Self-adaptation
- software performance
page: 117-122
place: New York, NY, USA
publication: '{Proceedings of the 8th International ACM SIGSOFT Conference on Quality
of Software Architectures (QoSA)}'
publication_identifier:
isbn:
- 978-1-4503-1346-9
publisher: ACM
status: public
title: 'Model-driven Performance Engineering of Self-adaptive Systems: A Survey'
type: conference
user_id: '4870'
year: '2012'
...
---
_id: '9783'
abstract:
- lang: eng
text: To optimize the ultrasound irradiation for cavitation based ultrasound applications
like sonochemistry or ultrasound cleaning, the correlation between cavitation
intensity and the resulting effect on the process is of interest. Furthermore,
changing conditions like temperature and pressure result in varying acoustic properties
of the liquid. That might necessitate an adaption of the ultrasound irradiation.
To detect such changes during operation, process monitoring is desired. Labor
intensive processes, that might be carried out for several hours, also require
process monitoring to increase their reliability by detection of changes or malfunctions
during operation. In some applications cavitation detection and monitoring can
be achieved by the application of sensors in the sound field. Though the application
of sensors is possible, this necessitates modifications on the system and the
sensor might disturb the sound field. In other applications harsh, process conditions
prohibit the application of sensors in the sound field. Therefore alternative
techniques for cavitation detection and monitoring are desired. The applicability
of an external microphone and a self-sensing ultrasound transducer for cavitation
detection were experimentally investigated. Both methods were found to be suitable
and easily applicable.
author:
- first_name: Peter
full_name: Bornmann, Peter
last_name: Bornmann
- first_name: Tobias
full_name: Hemsel, Tobias
id: '210'
last_name: Hemsel
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
- first_name: Takafumi
full_name: Maeda, Takafumi
last_name: Maeda
- first_name: Takeshi
full_name: Morita, Takeshi
last_name: Morita
citation:
ama: 'Bornmann P, Hemsel T, Sextro W, Maeda T, Morita T. Non-perturbing cavitation
detection / monitoring in sonochemical reactors. In: Ultrasonics Symposium
(IUS), 2012 IEEE International. ; 2012:1141-1144. doi:10.1109/ULTSYM.2012.0284'
apa: Bornmann, P., Hemsel, T., Sextro, W., Maeda, T., & Morita, T. (2012). Non-perturbing
cavitation detection / monitoring in sonochemical reactors. In Ultrasonics
Symposium (IUS), 2012 IEEE International (pp. 1141–1144). https://doi.org/10.1109/ULTSYM.2012.0284
bibtex: '@inproceedings{Bornmann_Hemsel_Sextro_Maeda_Morita_2012, title={Non-perturbing
cavitation detection / monitoring in sonochemical reactors}, DOI={10.1109/ULTSYM.2012.0284},
booktitle={Ultrasonics Symposium (IUS), 2012 IEEE International}, author={Bornmann,
Peter and Hemsel, Tobias and Sextro, Walter and Maeda, Takafumi and Morita, Takeshi},
year={2012}, pages={1141–1144} }'
chicago: Bornmann, Peter, Tobias Hemsel, Walter Sextro, Takafumi Maeda, and Takeshi
Morita. “Non-Perturbing Cavitation Detection / Monitoring in Sonochemical Reactors.”
In Ultrasonics Symposium (IUS), 2012 IEEE International, 1141–44, 2012.
https://doi.org/10.1109/ULTSYM.2012.0284.
ieee: P. Bornmann, T. Hemsel, W. Sextro, T. Maeda, and T. Morita, “Non-perturbing
cavitation detection / monitoring in sonochemical reactors,” in Ultrasonics
Symposium (IUS), 2012 IEEE International, 2012, pp. 1141–1144.
mla: Bornmann, Peter, et al. “Non-Perturbing Cavitation Detection / Monitoring in
Sonochemical Reactors.” Ultrasonics Symposium (IUS), 2012 IEEE International,
2012, pp. 1141–44, doi:10.1109/ULTSYM.2012.0284.
short: 'P. Bornmann, T. Hemsel, W. Sextro, T. Maeda, T. Morita, in: Ultrasonics
Symposium (IUS), 2012 IEEE International, 2012, pp. 1141–1144.'
date_created: 2019-05-13T13:18:49Z
date_updated: 2022-01-06T07:04:20Z
department:
- _id: '151'
doi: 10.1109/ULTSYM.2012.0284
keyword:
- cavitation
- chemical reactors
- microphones
- process monitoring
- reliability
- ultrasonic applications
- ultrasonic waves
- acoustic properties
- cavitation based ultrasound applications
- cavitation intensity
- change detection reliability
- external microphone
- malfunction detection reliability
- nonperturbing cavitation detection
- nonperturbing cavitation monitoring
- process monitoring
- self-sensing ultrasound transducer
- sonochemical reactors
- sonochemistry
- ultrasound cleaning
- ultrasound irradiation
- Acoustics
- Liquids
- Monitoring
- Sensors
- Sonar equipment
- Transducers
- Ultrasonic imaging
language:
- iso: eng
page: 1141-1144
publication: Ultrasonics Symposium (IUS), 2012 IEEE International
publication_identifier:
issn:
- 1948-5719
quality_controlled: '1'
status: public
title: Non-perturbing cavitation detection / monitoring in sonochemical reactors
type: conference
user_id: '55222'
year: '2012'
...
---
_id: '9784'
abstract:
- lang: eng
text: Piezoelectric inertia motors use the inertia of a body to drive it by means
of a friction contact in a series of small steps. These motors can operate in
``stick-slip'' or ``slip-slip'' mode, with the fundamental frequency of the driving
signal ranging from several Hertz to more than 100 kHz. To predict the motor characteristics,
a Coulomb friction model is sufficient in many cases, but numerical simulation
requires microscopic time steps. This contribution proposes a much faster simulation
technique using one evaluation per period of the excitation signal. The proposed
technique produces results very close to those of timestep simulation for ultrasonics
inertia motors and allows direct determination of the steady-state velocity of
an inertia motor from the motion profile of the driving part. Thus it is a useful
simulation technique which can be applied in both analysis and design of inertia
motors, especially for parameter studies and optimisation.
author:
- first_name: Matthias
full_name: Hunstig, Matthias
last_name: Hunstig
- first_name: Tobias
full_name: Hemsel, Tobias
last_name: Hemsel
- first_name: Walter
full_name: Sextro, Walter
last_name: Sextro
citation:
ama: 'Hunstig M, Hemsel T, Sextro W. An efficient simulation technique for high-frequency
piezoelectric inertia motors. In: Ultrasonics Symposium (IUS), 2012 IEEE International.
; 2012:277-280. doi:10.1109/ULTSYM.2012.0068'
apa: Hunstig, M., Hemsel, T., & Sextro, W. (2012). An efficient simulation technique
for high-frequency piezoelectric inertia motors. In Ultrasonics Symposium (IUS),
2012 IEEE International (pp. 277–280). https://doi.org/10.1109/ULTSYM.2012.0068
bibtex: '@inproceedings{Hunstig_Hemsel_Sextro_2012, title={An efficient simulation
technique for high-frequency piezoelectric inertia motors}, DOI={10.1109/ULTSYM.2012.0068},
booktitle={Ultrasonics Symposium (IUS), 2012 IEEE International}, author={Hunstig,
Matthias and Hemsel, Tobias and Sextro, Walter}, year={2012}, pages={277–280}
}'
chicago: Hunstig, Matthias, Tobias Hemsel, and Walter Sextro. “An Efficient Simulation
Technique for High-Frequency Piezoelectric Inertia Motors.” In Ultrasonics
Symposium (IUS), 2012 IEEE International, 277–80, 2012. https://doi.org/10.1109/ULTSYM.2012.0068.
ieee: M. Hunstig, T. Hemsel, and W. Sextro, “An efficient simulation technique for
high-frequency piezoelectric inertia motors,” in Ultrasonics Symposium (IUS),
2012 IEEE International, 2012, pp. 277–280.
mla: Hunstig, Matthias, et al. “An Efficient Simulation Technique for High-Frequency
Piezoelectric Inertia Motors.” Ultrasonics Symposium (IUS), 2012 IEEE International,
2012, pp. 277–80, doi:10.1109/ULTSYM.2012.0068.
short: 'M. Hunstig, T. Hemsel, W. Sextro, in: Ultrasonics Symposium (IUS), 2012
IEEE International, 2012, pp. 277–280.'
date_created: 2019-05-13T13:20:17Z
date_updated: 2022-01-06T07:04:20Z
department:
- _id: '151'
doi: 10.1109/ULTSYM.2012.0068
keyword:
- friction
- ultrasonic motors
- Coulomb friction model
- efficient simulation technique
- friction contact
- high-frequency piezoelectric inertia motor
- motor characteristics prediction
- numerical simulation
- slip-slip mode
- stick-slip mode
- time-step simulation
- ultrasonic inertia motor
- Acceleration
- Acoustics
- Actuators
- Computational modeling
- Friction
- Numerical models
- Steady-state
language:
- iso: eng
page: 277-280
publication: Ultrasonics Symposium (IUS), 2012 IEEE International
publication_identifier:
issn:
- 1948-5719
quality_controlled: '1'
status: public
title: An efficient simulation technique for high-frequency piezoelectric inertia
motors
type: conference
user_id: '55222'
year: '2012'
...
---
_id: '11864'
abstract:
- lang: eng
text: In this work, an observation model for the joint compensation of noise and
reverberation in the logarithmic mel power spectral density domain is considered.
It relates the features of the noisy reverberant speech to those of the non-reverberant
speech and the noise. In contrast to enhancement of features only corrupted by
reverberation (reverberant features), enhancement of noisy reverberant features
requires a more sophisticated model for the error introduced by the proposed observation
model. In a first consideration, it will be shown that this error is highly dependent
on the instantaneous ratio of the power of reverberant speech to the power of
the noise and, moreover, sensitive to the phase between reverberant speech and
noise in the short-time discrete Fourier domain. Afterwards, a statistically motivated
approach will be presented allowing for the model of the observation error to
be inferred from the error model previously used for the reverberation only case.
Finally, the developed observation error model will be utilized in a Bayesian
feature enhancement scheme, leading to improvements in word accuracy on the AURORA5
database.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Leutnant V, Krueger A, Haeb-Umbach R. A Statistical Observation Model For
Noisy Reverberant Speech Features and its Application to Robust ASR. In: Signal
Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference
On. ; 2012.'
apa: Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2012). A Statistical Observation
Model For Noisy Reverberant Speech Features and its Application to Robust ASR.
In Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International
Conference on.
bibtex: '@inproceedings{Leutnant_Krueger_Haeb-Umbach_2012, title={A Statistical
Observation Model For Noisy Reverberant Speech Features and its Application to
Robust ASR}, booktitle={Signal Processing, Communications and Computing (ICSPCC),
2012 IEEE International Conference on}, author={Leutnant, Volker and Krueger,
Alexander and Haeb-Umbach, Reinhold}, year={2012} }'
chicago: Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “A Statistical
Observation Model For Noisy Reverberant Speech Features and Its Application to
Robust ASR.” In Signal Processing, Communications and Computing (ICSPCC), 2012
IEEE International Conference On, 2012.
ieee: V. Leutnant, A. Krueger, and R. Haeb-Umbach, “A Statistical Observation Model
For Noisy Reverberant Speech Features and its Application to Robust ASR,” in Signal
Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference
on, 2012.
mla: Leutnant, Volker, et al. “A Statistical Observation Model For Noisy Reverberant
Speech Features and Its Application to Robust ASR.” Signal Processing, Communications
and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.
short: 'V. Leutnant, A. Krueger, R. Haeb-Umbach, in: Signal Processing, Communications
and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.'
date_created: 2019-07-12T05:29:44Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
keyword:
- Robust Automatic Speech Recognition
- Bayesian feature enhancement
- observation model for reverberant and noisy speech
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6335731
oa: '1'
publication: Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International
Conference on
status: public
title: A Statistical Observation Model For Noisy Reverberant Speech Features and its
Application to Robust ASR
type: conference
user_id: '44006'
year: '2012'
...
---
_id: '11845'
abstract:
- lang: eng
text: The paper proposes a modification of the standard maximum a posteriori (MAP)
method for the estimation of the parameters of a Gaussian process for cases where
the process is superposed by additive Gaussian observation errors of known variance.
Simulations on artificially generated data demonstrate the superiority of the
proposed method. While reducing to the ordinary MAP approach in the absence of
observation noise, the improvement becomes the more pronounced the larger the
variance of the observation noise. The method is further extended to track the
parameters in case of non-stationary Gaussian processes.
author:
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Krueger A, Haeb-Umbach R. MAP-based estimation of the parameters of non-stationary
Gaussian processes from noisy observations. In: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2011). ; 2011:3596-3599.
doi:10.1109/ICASSP.2011.5946256'
apa: Krueger, A., & Haeb-Umbach, R. (2011). MAP-based estimation of the parameters
of non-stationary Gaussian processes from noisy observations. In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2011) (pp. 3596–3599).
https://doi.org/10.1109/ICASSP.2011.5946256
bibtex: '@inproceedings{Krueger_Haeb-Umbach_2011, title={MAP-based estimation of
the parameters of non-stationary Gaussian processes from noisy observations},
DOI={10.1109/ICASSP.2011.5946256},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2011)}, author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2011},
pages={3596–3599} }'
chicago: Krueger, Alexander, and Reinhold Haeb-Umbach. “MAP-Based Estimation of
the Parameters of Non-Stationary Gaussian Processes from Noisy Observations.”
In IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2011), 3596–99, 2011. https://doi.org/10.1109/ICASSP.2011.5946256.
ieee: A. Krueger and R. Haeb-Umbach, “MAP-based estimation of the parameters of
non-stationary Gaussian processes from noisy observations,” in IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011,
pp. 3596–3599.
mla: Krueger, Alexander, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the
Parameters of Non-Stationary Gaussian Processes from Noisy Observations.” IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011),
2011, pp. 3596–99, doi:10.1109/ICASSP.2011.5946256.
short: 'A. Krueger, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.'
date_created: 2019-07-12T05:29:22Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2011.5946256
keyword:
- Gaussian processes
- MAP-based estimation
- maximum a posteriori method
- maximum likelihood estimation
- nonstationary Gaussian processes
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2011/KrHa11.pdf
oa: '1'
page: 3596-3599
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2011)
status: public
title: MAP-based estimation of the parameters of non-stationary Gaussian processes
from noisy observations
type: conference
user_id: '44006'
year: '2011'
...
---
_id: '11850'
abstract:
- lang: eng
text: In this paper, we present a novel blocking matrix and fixed beamformer design
for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure.
They are based on a new method for estimating the acoustical transfer function
ratios in the presence of stationary noise. The estimation method relies on solving
a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector
tracking utilizing the power iteration method is employed and shown to achieve
a high convergence speed. Simulation results demonstrate that the proposed beamformer
leads to better noise and interference reduction and reduced speech distortions
compared to other blocking matrix designs from the literature.
author:
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Krueger A, Warsitz E, Haeb-Umbach R. Speech Enhancement With a GSC-Like Structure
Employing Eigenvector-Based Transfer Function Ratios Estimation. IEEE Transactions
on Audio, Speech, and Language Processing. 2011;19(1):206-219. doi:10.1109/TASL.2010.2047324
apa: Krueger, A., Warsitz, E., & Haeb-Umbach, R. (2011). Speech Enhancement
With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios
Estimation. IEEE Transactions on Audio, Speech, and Language Processing,
19(1), 206–219. https://doi.org/10.1109/TASL.2010.2047324
bibtex: '@article{Krueger_Warsitz_Haeb-Umbach_2011, title={Speech Enhancement With
a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation},
volume={19}, DOI={10.1109/TASL.2010.2047324},
number={1}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2011},
pages={206–219} }'
chicago: 'Krueger, Alexander, Ernst Warsitz, and Reinhold Haeb-Umbach. “Speech Enhancement
With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios
Estimation.” IEEE Transactions on Audio, Speech, and Language Processing
19, no. 1 (2011): 206–19. https://doi.org/10.1109/TASL.2010.2047324.'
ieee: A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like
Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” IEEE
Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, pp.
206–219, 2011.
mla: Krueger, Alexander, et al. “Speech Enhancement With a GSC-Like Structure Employing
Eigenvector-Based Transfer Function Ratios Estimation.” IEEE Transactions on
Audio, Speech, and Language Processing, vol. 19, no. 1, 2011, pp. 206–19,
doi:10.1109/TASL.2010.2047324.
short: A. Krueger, E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech,
and Language Processing 19 (2011) 206–219.
date_created: 2019-07-12T05:29:28Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2010.2047324
intvolume: ' 19'
issue: '1'
keyword:
- acoustical transfer function ratio
- adaptive eigenvector tracking
- array signal processing
- beamformer design
- blocking matrix
- eigenvalues and eigenfunctions
- eigenvector-based transfer function ratios estimation
- generalized sidelobe canceler
- interference reduction
- iterative methods
- power iteration method
- reduced speech distortions
- reverberant enclosure
- reverberation
- speech enhancement
- stationary noise
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2011/KrWaHa11.pdf
oa: '1'
page: 206-219
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer
Function Ratios Estimation
type: journal_article
user_id: '44006'
volume: 19
year: '2011'
...
---
_id: '11846'
abstract:
- lang: eng
text: In this paper, we present a new technique for automatic speech recognition
(ASR) in reverberant environments. Our approach is aimed at the enhancement of
the logarithmic Mel power spectrum, which is computed at an intermediate stage
to obtain the widely used Mel frequency cepstral coefficients (MFCCs). Given the
reverberant logarithmic Mel power spectral coefficients (LMPSCs), a minimum mean
square error estimate of the clean LMPSCs is computed by carrying out Bayesian
inference. We employ switching linear dynamical models as an a priori model for
the dynamics of the clean LMPSCs. Further, we derive a stochastic observation
model which relates the clean to the reverberant LMPSCs through a simplified model
of the room impulse response (RIR). This model requires only two parameters, namely
RIR energy and reverberation time, which can be estimated from the captured microphone
signal. The performance of the proposed enhancement technique is studied on the
AURORA5 database and compared to that of constrained maximum-likelihood linear
regression (CMLLR). It is shown by experimental results that our approach significantly
outperforms CMLLR and that up to 80\% of the errors caused by the reverberation
are recovered. In addition to the fact that the approach is compatible with the
standard MFCC feature vectors, it leaves the ASR back-end unchanged. It is of
moderate computational complexity and suitable for real time applications.
author:
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Krueger A, Haeb-Umbach R. Model-Based Feature Enhancement for Reverberant Speech
Recognition. IEEE Transactions on Audio, Speech, and Language Processing.
2010;18(7):1692-1707. doi:10.1109/TASL.2010.2049684
apa: Krueger, A., & Haeb-Umbach, R. (2010). Model-Based Feature Enhancement
for Reverberant Speech Recognition. IEEE Transactions on Audio, Speech, and
Language Processing, 18(7), 1692–1707. https://doi.org/10.1109/TASL.2010.2049684
bibtex: '@article{Krueger_Haeb-Umbach_2010, title={Model-Based Feature Enhancement
for Reverberant Speech Recognition}, volume={18}, DOI={10.1109/TASL.2010.2049684},
number={7}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2010}, pages={1692–1707}
}'
chicago: 'Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement
for Reverberant Speech Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing 18, no. 7 (2010): 1692–1707. https://doi.org/10.1109/TASL.2010.2049684.'
ieee: A. Krueger and R. Haeb-Umbach, “Model-Based Feature Enhancement for Reverberant
Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing,
vol. 18, no. 7, pp. 1692–1707, 2010.
mla: Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement
for Reverberant Speech Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing, vol. 18, no. 7, 2010, pp. 1692–707, doi:10.1109/TASL.2010.2049684.
short: A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 18 (2010) 1692–1707.
date_created: 2019-07-12T05:29:23Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2010.2049684
intvolume: ' 18'
issue: '7'
keyword:
- ASR
- AURORA5 database
- automatic speech recognition
- Bayesian inference
- belief networks
- CMLLR
- computational complexity
- constrained maximum likelihood linear regression
- least mean squares methods
- LMPSC computation
- logarithmic Mel power spectrum
- maximum likelihood estimation
- Mel frequency cepstral coefficients
- MFCC feature vectors
- microphone signal
- minimum mean square error estimation
- model-based feature enhancement
- regression analysis
- reverberant speech recognition
- reverberation
- RIR energy
- room impulse response
- speech recognition
- stochastic observation model
- stochastic processes
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/KrHa10.pdf
oa: '1'
page: 1692-1707
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Model-Based Feature Enhancement for Reverberant Speech Recognition
type: journal_article
user_id: '44006'
volume: 18
year: '2010'
...
---
_id: '11913'
abstract:
- lang: eng
text: In this paper we propose to employ directional statistics in a complex vector
space to approach the problem of blind speech separation in the presence of spatially
correlated noise. We interpret the values of the short time Fourier transform
of the microphone signals to be draws from a mixture of complex Watson distributions,
a probabilistic model which naturally accounts for spatial aliasing. The parameters
of the density are related to the a priori source probabilities, the power of
the sources and the transfer function ratios from sources to sensors. Estimation
formulas are derived for these parameters by employing the Expectation Maximization
(EM) algorithm. The E-step corresponds to the estimation of the source presence
probabilities for each time-frequency bin, while the M-step leads to a maximum
signal-to-noise ratio (MaxSNR) beamformer in the presence of uncertainty about
the source activity. Experimental results are reported for an implementation in
a generalized sidelobe canceller (GSC) like spatial beamforming configuration
for 3 speech sources with significant coherent noise in reverberant environments,
demonstrating the usefulness of the novel modeling framework.
author:
- first_name: Dang Hai
full_name: Tran Vu, Dang Hai
last_name: Tran Vu
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Tran Vu DH, Haeb-Umbach R. Blind speech separation employing directional statistics
in an Expectation Maximization framework. In: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2010). ; 2010:241-244.
doi:10.1109/ICASSP.2010.5495994'
apa: Tran Vu, D. H., & Haeb-Umbach, R. (2010). Blind speech separation employing
directional statistics in an Expectation Maximization framework. In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010) (pp. 241–244).
https://doi.org/10.1109/ICASSP.2010.5495994
bibtex: '@inproceedings{Tran Vu_Haeb-Umbach_2010, title={Blind speech separation
employing directional statistics in an Expectation Maximization framework}, DOI={10.1109/ICASSP.2010.5495994},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2010)}, author={Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2010},
pages={241–244} }'
chicago: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
Directional Statistics in an Expectation Maximization Framework.” In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 241–44,
2010. https://doi.org/10.1109/ICASSP.2010.5495994.
ieee: D. H. Tran Vu and R. Haeb-Umbach, “Blind speech separation employing directional
statistics in an Expectation Maximization framework,” in IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010,
pp. 241–244.
mla: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
Directional Statistics in an Expectation Maximization Framework.” IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010,
pp. 241–44, doi:10.1109/ICASSP.2010.5495994.
short: 'D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.'
date_created: 2019-07-12T05:30:40Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2010.5495994
keyword:
- array signal processing
- blind source separation
- blind speech separation
- complex vector space
- complex Watson distribution
- directional statistics
- expectation-maximisation algorithm
- expectation maximization algorithm
- Fourier transform
- Fourier transforms
- generalized sidelobe canceller
- interference suppression
- maximum signal-to-noise ratio beamformer
- microphone signal
- probabilistic model
- spatial aliasing
- spatial beamforming configuration
- speech enhancement
- statistical distributions
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-2.pdf
oa: '1'
page: 241-244
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2010)
status: public
title: Blind speech separation employing directional statistics in an Expectation
Maximization framework
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '37037'
abstract:
- lang: eng
text: Today we can identify a big gap between requirement specification and the
generation of test environments. This article extends the Classification Tree
Method for Embedded Systems (CTM/ES) to fill this gap by new concepts for the
precise specification of stimuli for operational ranges of continuous control
systems. It introduces novel means for continuous acceptance criteria definition
and for functional coverage definition.
author:
- first_name: Alexander
full_name: Krupp, Alexander
last_name: Krupp
- first_name: Wolfgang
full_name: Müller, Wolfgang
id: '16243'
last_name: Müller
citation:
ama: 'Krupp A, Müller W. A Systematic Approach to Combined HW/SW System Test. In:
Proceedings of DATE’10. IEEE; 2010. doi:10.1109/DATE.2010.5457186'
apa: Krupp, A., & Müller, W. (2010). A Systematic Approach to Combined HW/SW
System Test. Proceedings of DATE’10. Design, Automation & Test in Europe
Conference & Exhibition (DATE 2010), Dresden. https://doi.org/10.1109/DATE.2010.5457186
bibtex: '@inproceedings{Krupp_Müller_2010, place={Dresden}, title={A Systematic
Approach to Combined HW/SW System Test}, DOI={10.1109/DATE.2010.5457186},
booktitle={Proceedings of DATE’10}, publisher={IEEE}, author={Krupp, Alexander
and Müller, Wolfgang}, year={2010} }'
chicago: 'Krupp, Alexander, and Wolfgang Müller. “A Systematic Approach to Combined
HW/SW System Test.” In Proceedings of DATE’10. Dresden: IEEE, 2010. https://doi.org/10.1109/DATE.2010.5457186.'
ieee: 'A. Krupp and W. Müller, “A Systematic Approach to Combined HW/SW System Test,”
presented at the Design, Automation & Test in Europe Conference & Exhibition
(DATE 2010), Dresden, 2010, doi: 10.1109/DATE.2010.5457186.'
mla: Krupp, Alexander, and Wolfgang Müller. “A Systematic Approach to Combined HW/SW
System Test.” Proceedings of DATE’10, IEEE, 2010, doi:10.1109/DATE.2010.5457186.
short: 'A. Krupp, W. Müller, in: Proceedings of DATE’10, IEEE, Dresden, 2010.'
conference:
location: Dresden
name: Design, Automation & Test in Europe Conference & Exhibition (DATE 2010)
date_created: 2023-01-17T10:41:15Z
date_updated: 2023-01-17T10:41:25Z
department:
- _id: '672'
doi: 10.1109/DATE.2010.5457186
keyword:
- System testing
- Automatic testing
- Object oriented modeling
- Classification tree analysis
- Automotive engineering
- Mathematical model
- Embedded system
- Control systems
- Electronic equipment testing
- Software testing
language:
- iso: eng
place: Dresden
publication: Proceedings of DATE’10
publisher: IEEE
status: public
title: A Systematic Approach to Combined HW/SW System Test
type: conference
user_id: '5786'
year: '2010'
...
---
_id: '37057'
abstract:
- lang: eng
text: Many heterogeneous embedded systems, for example industrial automation and
automotive applications, require hard-real time constraints to be exhaustively
verified - which is a challenging task for the verification engineer. To cope
with complexity, verification techniques working on different abstraction levels
are best practice. SystemC is a versatile C++ based design and verification language,
offering various mechanisms and constructs required for embedded systems modeling.
Using the add-on SystemC Verification Library (SCV) elemental constrained-random
stimuli techniques may be used for verification. However, SCV has several drawbacks
such as lack of functional coverage. In this paper we present a functional coverage
library that implements parts of the IEEE 1800-2005 SystemVerilog standard and
allows capturing functional coverage throughout the design and verification process
with SystemC. Moreover, we will demonstrate the usability of the approach with
a case study working on a CAN bus model written in SystemC.
author:
- first_name: Gilles B.
full_name: Defo, Gilles B.
last_name: Defo
- first_name: Wolfgang
full_name: Müller, Wolfgang
id: '16243'
last_name: Müller
- first_name: Christoph
full_name: Kuznik, Christoph
last_name: Kuznik
citation:
ama: 'Defo GB, Müller W, Kuznik C. Verification of a CAN Bus Model in SystemC with
Functional Coverage. In: Proceedings of SIES 2010. IEEE; 2010. doi:10.1109/SIES.2010.5551379'
apa: Defo, G. B., Müller, W., & Kuznik, C. (2010). Verification of a CAN Bus
Model in SystemC with Functional Coverage. Proceedings of SIES 2010. International
Symposium on Industrial Embedded System (SIES), Trento, Italy. https://doi.org/10.1109/SIES.2010.5551379
bibtex: '@inproceedings{Defo_Müller_Kuznik_2010, place={ Trento, Italy}, title={Verification
of a CAN Bus Model in SystemC with Functional Coverage}, DOI={10.1109/SIES.2010.5551379},
booktitle={Proceedings of SIES 2010}, publisher={IEEE}, author={Defo, Gilles B.
and Müller, Wolfgang and Kuznik, Christoph}, year={2010} }'
chicago: 'Defo, Gilles B., Wolfgang Müller, and Christoph Kuznik. “Verification
of a CAN Bus Model in SystemC with Functional Coverage.” In Proceedings of
SIES 2010. Trento, Italy: IEEE, 2010. https://doi.org/10.1109/SIES.2010.5551379.'
ieee: 'G. B. Defo, W. Müller, and C. Kuznik, “Verification of a CAN Bus Model in
SystemC with Functional Coverage,” presented at the International Symposium on
Industrial Embedded System (SIES), Trento, Italy, 2010, doi: 10.1109/SIES.2010.5551379.'
mla: Defo, Gilles B., et al. “Verification of a CAN Bus Model in SystemC with Functional
Coverage.” Proceedings of SIES 2010, IEEE, 2010, doi:10.1109/SIES.2010.5551379.
short: 'G.B. Defo, W. Müller, C. Kuznik, in: Proceedings of SIES 2010, IEEE, Trento,
Italy, 2010.'
conference:
location: ' Trento, Italy'
name: International Symposium on Industrial Embedded System (SIES)
date_created: 2023-01-17T11:34:56Z
date_updated: 2023-01-17T11:35:03Z
department:
- _id: '672'
doi: 10.1109/SIES.2010.5551379
keyword:
- Libraries
- Generators
- Transfer functions
- Monitoring
- Computational modeling
- Driver circuits
- Adaptation model
language:
- iso: eng
place: ' Trento, Italy'
publication: Proceedings of SIES 2010
publication_identifier:
eisbn:
- 978-1-4244-5841-7
publisher: IEEE
status: public
title: Verification of a CAN Bus Model in SystemC with Functional Coverage
type: conference
user_id: '5786'
year: '2010'
...
---
_id: '11723'
abstract:
- lang: eng
text: In this paper we present a novel vehicle tracking algorithm, which is based
on multi-level sensor fusion of GPS (global positioning system) with Inertial
Measurement Unit sensor data. It is shown that the robustness of the system to
temporary dropouts of the GPS signal, which may occur due to limited visibility
of satellites in narrow street canyons or tunnels, is greatly improved by sensor
fusion. We further demonstrate how the observation and state noise covariances
of the employed Kalman filters can be estimated alongside the filtering by an
application of the Expectation-Maximization algorithm. The proposed time-variant
multi-level Kalman filter is shown to outperform an Interacting Multiple Model
approach while at the same time being computationally less demanding.
author:
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Bevermeier M, Peschke S, Haeb-Umbach R. Robust vehicle localization based
on multi-level sensor fusion and online parameter estimation. In: 6th Workshop
on Positioning Navigation and Communication (WPNC 2009). ; 2009:235-242. doi:10.1109/WPNC.2009.4907833'
apa: Bevermeier, M., Peschke, S., & Haeb-Umbach, R. (2009). Robust vehicle localization
based on multi-level sensor fusion and online parameter estimation. In 6th
Workshop on Positioning Navigation and Communication (WPNC 2009) (pp. 235–242).
https://doi.org/10.1109/WPNC.2009.4907833
bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Robust vehicle
localization based on multi-level sensor fusion and online parameter estimation},
DOI={10.1109/WPNC.2009.4907833},
booktitle={6th Workshop on Positioning Navigation and Communication (WPNC 2009)},
author={Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2009},
pages={235–242} }'
chicago: Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Robust Vehicle
Localization Based on Multi-Level Sensor Fusion and Online Parameter Estimation.”
In 6th Workshop on Positioning Navigation and Communication (WPNC 2009),
235–42, 2009. https://doi.org/10.1109/WPNC.2009.4907833.
ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Robust vehicle localization
based on multi-level sensor fusion and online parameter estimation,” in 6th
Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp.
235–242.
mla: Bevermeier, Maik, et al. “Robust Vehicle Localization Based on Multi-Level
Sensor Fusion and Online Parameter Estimation.” 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 2009, pp. 235–42, doi:10.1109/WPNC.2009.4907833.
short: 'M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 2009, pp. 235–242.'
date_created: 2019-07-12T05:27:01Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
doi: 10.1109/WPNC.2009.4907833
keyword:
- covariance matrices
- expectation-maximisation algorithm
- expectation-maximization algorithm
- global positioning system
- Global Positioning System
- GPS
- inertial measurement unit
- interacting multiple model approach
- Kalman filters
- multilevel sensor fusion
- narrow street canyons
- narrow tunnels
- online parameter estimation
- parameter estimation
- road vehicles
- robust vehicle localization
- sensor fusion
- state noise covariances
- time-variant multilevel Kalman filter
- vehicle tracking algorithm
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09.pdf
oa: '1'
page: 235-242
publication: 6th Workshop on Positioning Navigation and Communication (WPNC 2009)
status: public
title: Robust vehicle localization based on multi-level sensor fusion and online parameter
estimation
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11724'
abstract:
- lang: eng
text: In this paper we present a novel vehicle tracking method which is based on
multi-stage Kalman filtering of GPS and IMU sensor data. After individual Kalman
filtering of GPS and IMU measurements the estimates of the orientation of the
vehicle are combined in an optimal manner to improve the robustness towards drift
errors. The tracking algorithm incorporates the estimation of time-variant covariance
parameters by using an iterative block Expectation-Maximization algorithm to account
for time-variant driving conditions and measurement quality. The proposed system
is compared to an interacting multiple model approach (IMM) and achieves improved
localization accuracy at lower computational complexity. Furthermore we show how
the joint parameter estimation and localizaiton can be conducted with streaming
input data to be able to track vehicles in a real driving environment.
author:
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Bevermeier M, Peschke S, Haeb-Umbach R. Joint Parameter Estimation and Tracking
in a Multi-Stage Kalman Filter for Vehicle Positioning. In: IEEE 69th Vehicular
Technology Conference (VTC 2009 Spring). ; 2009:1-5. doi:10.1109/VETECS.2009.5073634'
apa: Bevermeier, M., Peschke, S., & Haeb-Umbach, R. (2009). Joint Parameter
Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.
In IEEE 69th Vehicular Technology Conference (VTC 2009 Spring) (pp. 1–5).
https://doi.org/10.1109/VETECS.2009.5073634
bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Joint Parameter
Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning},
DOI={10.1109/VETECS.2009.5073634},
booktitle={IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)}, author={Bevermeier,
Maik and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2009}, pages={1–5} }'
chicago: Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Joint Parameter
Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.”
In IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 1–5, 2009.
https://doi.org/10.1109/VETECS.2009.5073634.
ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Joint Parameter Estimation
and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning,” in IEEE
69th Vehicular Technology Conference (VTC 2009 Spring), 2009, pp. 1–5.
mla: Bevermeier, Maik, et al. “Joint Parameter Estimation and Tracking in a Multi-Stage
Kalman Filter for Vehicle Positioning.” IEEE 69th Vehicular Technology Conference
(VTC 2009 Spring), 2009, pp. 1–5, doi:10.1109/VETECS.2009.5073634.
short: 'M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: IEEE 69th Vehicular Technology
Conference (VTC 2009 Spring), 2009, pp. 1–5.'
date_created: 2019-07-12T05:27:02Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
doi: 10.1109/VETECS.2009.5073634
keyword:
- computational complexity
- expectation-maximisation algorithm
- Global Positioning System
- inertial measurement unit
- inertial navigation
- interacting multiple model
- iterative block expectation-maximization algorithm
- Kalman filters
- multi-stage Kalman filter
- parameter estimation
- road vehicles
- vehicle positioning
- vehicle tracking
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09-1.pdf
oa: '1'
page: 1-5
publication: IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)
status: public
title: Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for
Vehicle Positioning
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11937'
abstract:
- lang: eng
text: In automatic speech recognition, hidden Markov models (HMMs) are commonly
used for speech decoding, while switching linear dynamic models (SLDMs) can be
employed for a preceding model-based speech feature enhancement. In this paper,
these model types are combined in order to obtain a novel iterative speech feature
enhancement and recognition architecture. It is shown that speech feature enhancement
with SLDMs can be improved by feeding back information from the HMM to the enhancement
stage. Two different feedback structures are derived. In the first, the posteriors
of the HMM states are used to control the model probabilities of the SLDMs, while
in the second they are employed to directly influence the estimate of the speech
feature distribution. Both approaches lead to improvements in recognition accuracy
both on the AURORA2 and AURORA4 databases compared to non-iterative speech feature
enhancement with SLDMs. It is also shown that a combination with uncertainty decoding
further enhances performance.
author:
- first_name: Stefan
full_name: Windmann, Stefan
last_name: Windmann
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Windmann S, Haeb-Umbach R. Approaches to Iterative Speech Feature Enhancement
and Recognition. IEEE Transactions on Audio, Speech, and Language Processing.
2009;17(5):974-984. doi:10.1109/TASL.2009.2014894
apa: Windmann, S., & Haeb-Umbach, R. (2009). Approaches to Iterative Speech
Feature Enhancement and Recognition. IEEE Transactions on Audio, Speech, and
Language Processing, 17(5), 974–984. https://doi.org/10.1109/TASL.2009.2014894
bibtex: '@article{Windmann_Haeb-Umbach_2009, title={Approaches to Iterative Speech
Feature Enhancement and Recognition}, volume={17}, DOI={10.1109/TASL.2009.2014894},
number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={974–984}
}'
chicago: 'Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech
Feature Enhancement and Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing 17, no. 5 (2009): 974–84. https://doi.org/10.1109/TASL.2009.2014894.'
ieee: S. Windmann and R. Haeb-Umbach, “Approaches to Iterative Speech Feature Enhancement
and Recognition,” IEEE Transactions on Audio, Speech, and Language Processing,
vol. 17, no. 5, pp. 974–984, 2009.
mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech
Feature Enhancement and Recognition.” IEEE Transactions on Audio, Speech, and
Language Processing, vol. 17, no. 5, 2009, pp. 974–84, doi:10.1109/TASL.2009.2014894.
short: S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 17 (2009) 974–984.
date_created: 2019-07-12T05:31:08Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/TASL.2009.2014894
intvolume: ' 17'
issue: '5'
keyword:
- AURORA2 databases
- AURORA4 databases
- automatic speech recognition
- feedback structures
- hidden Markov models
- HMM
- iterative methods
- iterative speech feature enhancement
- model probabilities
- speech decoding
- speech enhancement
- speech feature distribution
- speech recognition
- switching linear dynamic models
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-1.pdf
oa: '1'
page: 974-984
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Approaches to Iterative Speech Feature Enhancement and Recognition
type: journal_article
user_id: '44006'
volume: 17
year: '2009'
...
---
_id: '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'
...