---
_id: '9456'
abstract:
- lang: eng
text: In this paper we present our experimental results about classifying audio
data into broad acoustic categories. The reverberated sound samples from indoor
recordings are grouped into four classes, namely speech, music, acoustic events
and noise. We investigated a total of 188 acoustic features and achieved for the
best configuration a classification accuracy better than 98\%. This was achieved
by a 42-dimensional feature vector consisting of Mel-Frequency Cepstral Coefficients,
an autocorrelation feature and so-called track features that measure the length
of ''traces'' of high energy in the spectrogram. We also found a 4-feature configuration
with a classification rate of about 90\% allowing for broad acoustic category
classification with low computational effort.
author:
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Markus
full_name: Bartek, Markus
last_name: Bartek
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Schmalenstroeer J, Bartek M, Haeb-Umbach R. Investigations into Features for
Robust Classification into Broad Acoustic Categories. In: 37. Deutsche Jahrestagung
Fuer Akustik (DAGA 2011). ; 2011.'
apa: Schmalenstroeer, J., Bartek, M., & Haeb-Umbach, R. (2011). Investigations
into Features for Robust Classification into Broad Acoustic Categories. 37.
Deutsche Jahrestagung Fuer Akustik (DAGA 2011).
bibtex: '@inproceedings{Schmalenstroeer_Bartek_Haeb-Umbach_2011, title={Investigations
into Features for Robust Classification into Broad Acoustic Categories}, booktitle={37.
Deutsche Jahrestagung fuer Akustik (DAGA 2011)}, author={Schmalenstroeer, Joerg
and Bartek, Markus and Haeb-Umbach, Reinhold}, year={2011} }'
chicago: Schmalenstroeer, Joerg, Markus Bartek, and Reinhold Haeb-Umbach. “Investigations
into Features for Robust Classification into Broad Acoustic Categories.” In 37.
Deutsche Jahrestagung Fuer Akustik (DAGA 2011), 2011.
ieee: J. Schmalenstroeer, M. Bartek, and R. Haeb-Umbach, “Investigations into Features
for Robust Classification into Broad Acoustic Categories,” 2011.
mla: Schmalenstroeer, Joerg, et al. “Investigations into Features for Robust Classification
into Broad Acoustic Categories.” 37. Deutsche Jahrestagung Fuer Akustik (DAGA
2011), 2011.
short: 'J. Schmalenstroeer, M. Bartek, R. Haeb-Umbach, in: 37. Deutsche Jahrestagung
Fuer Akustik (DAGA 2011), 2011.'
date_created: 2019-04-25T14:36:02Z
date_updated: 2023-10-26T08:15:44Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2011/ScBaHa11-1.pdf
oa: '1'
publication: 37. Deutsche Jahrestagung fuer Akustik (DAGA 2011)
quality_controlled: '1'
status: public
title: Investigations into Features for Robust Classification into Broad Acoustic
Categories
type: conference
user_id: '460'
year: '2011'
...
---
_id: '11726'
abstract:
- lang: eng
text: In this paper we present a robust location estimation algorithm especially
focused on the accuracy in vertical position. A loosely-coupled error state space
Kalman filter, which fuses sensor data of an Inertial Measurement Unit and the
output of a Global Positioning System device, is augmented by height information
from an altitude measurement unit. This unit consists of a barometric altimeter
whose output is fused with topographic map information by a Kalman filter to provide
robust information about the current vertical user position. These data replace
the less reliable vertical position information provided the GPS device. It is
shown that typical barometric errors like thermal divergences and fluctuations
in the pressure due to changing weather conditions can be compensated by the topographic
map information and the barometric error Kalman filter. The resulting height information
is shown not only to be more reliable than height information provided by GPS.
It also turns out that it leads to better attitude and thus better overall localization
estimation accuracy due to the coupling of spatial orientations via the Direct
Cosine Matrix. Results are presented both for artificially generated and field
test data, where the user is moving by car.
author:
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Oliver
full_name: Walter, Oliver
last_name: Walter
- 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, Walter O, Peschke S, Haeb-Umbach R. Barometric height estimation
combined with map-matching in a loosely-coupled Kalman-filter. In: 7th Workshop
on Positioning Navigation and Communication (WPNC 2010). ; 2010:128-134. doi:10.1109/WPNC.2010.5650745'
apa: Bevermeier, M., Walter, O., Peschke, S., & Haeb-Umbach, R. (2010). Barometric
height estimation combined with map-matching in a loosely-coupled Kalman-filter.
In 7th Workshop on Positioning Navigation and Communication (WPNC 2010)
(pp. 128–134). https://doi.org/10.1109/WPNC.2010.5650745
bibtex: '@inproceedings{Bevermeier_Walter_Peschke_Haeb-Umbach_2010, title={Barometric
height estimation combined with map-matching in a loosely-coupled Kalman-filter},
DOI={10.1109/WPNC.2010.5650745},
booktitle={7th Workshop on Positioning Navigation and Communication (WPNC 2010)},
author={Bevermeier, Maik and Walter, Oliver and Peschke, Sven and Haeb-Umbach,
Reinhold}, year={2010}, pages={128–134} }'
chicago: Bevermeier, Maik, Oliver Walter, Sven Peschke, and Reinhold Haeb-Umbach.
“Barometric Height Estimation Combined with Map-Matching in a Loosely-Coupled
Kalman-Filter.” In 7th Workshop on Positioning Navigation and Communication
(WPNC 2010), 128–34, 2010. https://doi.org/10.1109/WPNC.2010.5650745.
ieee: M. Bevermeier, O. Walter, S. Peschke, and R. Haeb-Umbach, “Barometric height
estimation combined with map-matching in a loosely-coupled Kalman-filter,” in
7th Workshop on Positioning Navigation and Communication (WPNC 2010), 2010,
pp. 128–134.
mla: Bevermeier, Maik, et al. “Barometric Height Estimation Combined with Map-Matching
in a Loosely-Coupled Kalman-Filter.” 7th Workshop on Positioning Navigation
and Communication (WPNC 2010), 2010, pp. 128–34, doi:10.1109/WPNC.2010.5650745.
short: 'M. Bevermeier, O. Walter, S. Peschke, R. Haeb-Umbach, in: 7th Workshop on
Positioning Navigation and Communication (WPNC 2010), 2010, pp. 128–134.'
date_created: 2019-07-12T05:27:04Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
doi: 10.1109/WPNC.2010.5650745
keyword:
- altitude measurement unit
- barometers
- barometric altimeter
- barometric error Kalman filter
- barometric height estimation
- direct cosine matrix
- global positioning system
- Global Positioning System
- GPS device
- height information
- height measurement
- inertial measurement unit
- Kalman filters
- loosely-coupled error state space Kalman filter
- loosely-coupled Kalman-filter
- map matching
- robust information
- robust location estimation
- sensor fusion
- topographic map information
- vertical user position
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/BeWaPeHa10.pdf
oa: '1'
page: 128-134
publication: 7th Workshop on Positioning Navigation and Communication (WPNC 2010)
status: public
title: Barometric height estimation combined with map-matching in a loosely-coupled
Kalman-filter
type: conference
user_id: '44006'
year: '2010'
...
---
_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: '11857'
abstract:
- lang: eng
text: Traditionally, ASR systems are based on hidden Markov models with Gaussian
mixtures modelling the state-conditioned feature distribution. The inherent assumption
of conditional independence, stating that a feature's likelihood solely depends
on the current HMM state, makes the search computationally tractable, nevertheless
has also been identified to be a major reason for the lack of robustness of such
systems. Linear dynamic models have been proposed to overcome this weakness by
employing a hidden dynamic state process underlying the observed features. Though
performance of linear dynamic models on continuous speech/phone recognition tasks
has been shown to be superior to that of equivalent static models, this approach
still cannot compete with the established acoustic models. In this paper we consider
the combination of hidden Markov models based on Gaussian mixture densities (GMM-HMMs)
and linear dynamic models (LDMs) as the acoustic model for automatic speech recognition
systems. In doing so, the individual strengths of both models, i.e. the modelling
of long-term temporal dependencies by the GMM-HMM and the direct modelling of
statistical dependencies between consecutive feature vectors by the LDM, are exploited.
Phone classification experiments conducted on the TIMIT database indicate the
prospective use of this approach for the application to continuous speech recognition.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Leutnant V, Haeb-Umbach R. Options for Modelling Temporal Statistical Dependencies
in an Acoustic Model for ASR. In: 36. Deutsche Jahrestagung Fuer Akustik (DAGA
2010). ; 2010.'
apa: Leutnant, V., & Haeb-Umbach, R. (2010). Options for Modelling Temporal
Statistical Dependencies in an Acoustic Model for ASR. In 36. Deutsche Jahrestagung
fuer Akustik (DAGA 2010).
bibtex: '@inproceedings{Leutnant_Haeb-Umbach_2010, title={Options for Modelling
Temporal Statistical Dependencies in an Acoustic Model for ASR}, booktitle={36.
Deutsche Jahrestagung fuer Akustik (DAGA 2010)}, author={Leutnant, Volker and
Haeb-Umbach, Reinhold}, year={2010} }'
chicago: Leutnant, Volker, and Reinhold Haeb-Umbach. “Options for Modelling Temporal
Statistical Dependencies in an Acoustic Model for ASR.” In 36. Deutsche Jahrestagung
Fuer Akustik (DAGA 2010), 2010.
ieee: V. Leutnant and R. Haeb-Umbach, “Options for Modelling Temporal Statistical
Dependencies in an Acoustic Model for ASR,” in 36. Deutsche Jahrestagung fuer
Akustik (DAGA 2010), 2010.
mla: Leutnant, Volker, and Reinhold Haeb-Umbach. “Options for Modelling Temporal
Statistical Dependencies in an Acoustic Model for ASR.” 36. Deutsche Jahrestagung
Fuer Akustik (DAGA 2010), 2010.
short: 'V. Leutnant, R. Haeb-Umbach, in: 36. Deutsche Jahrestagung Fuer Akustik
(DAGA 2010), 2010.'
date_created: 2019-07-12T05:29:36Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/LeHa10-1.pdf
oa: '1'
publication: 36. Deutsche Jahrestagung fuer Akustik (DAGA 2010)
status: public
title: Options for Modelling Temporal Statistical Dependencies in an Acoustic Model
for ASR
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '11858'
abstract:
- lang: eng
text: Linear dynamic models (LDMs) have been shown to be a viable alternative to
hidden Markov models (HMMs) on small-vocabulary recognition tasks, such as phone
classification. In this paper we investigate various statistical model combination
approaches for a hybrid HMM-LDM recognizer, resulting in a phone classification
performance that outperforms the best individual classifier. Further, we report
on continuous speech recognition experiments on the AURORA4 corpus, where the
model combination is carried out on wordgraph rescoring. While the hybrid system
improves the HMM system in the case of monophone HMMs, the performance of the
triphone HMM model could not be improved by monophone LDMs, asking for the need
to introduce context-dependency also in the LDM model inventory.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Leutnant V, Haeb-Umbach R. On the Exploitation of Hidden Markov Models and
Linear Dynamic Models in a Hybrid Decoder Architecture for Continuous Speech Recognition.
In: Interspeech 2010. ; 2010.'
apa: Leutnant, V., & Haeb-Umbach, R. (2010). On the Exploitation of Hidden Markov
Models and Linear Dynamic Models in a Hybrid Decoder Architecture for Continuous
Speech Recognition. In Interspeech 2010.
bibtex: '@inproceedings{Leutnant_Haeb-Umbach_2010, title={On the Exploitation of
Hidden Markov Models and Linear Dynamic Models in a Hybrid Decoder Architecture
for Continuous Speech Recognition}, booktitle={Interspeech 2010}, author={Leutnant,
Volker and Haeb-Umbach, Reinhold}, year={2010} }'
chicago: Leutnant, Volker, and Reinhold Haeb-Umbach. “On the Exploitation of Hidden
Markov Models and Linear Dynamic Models in a Hybrid Decoder Architecture for Continuous
Speech Recognition.” In Interspeech 2010, 2010.
ieee: V. Leutnant and R. Haeb-Umbach, “On the Exploitation of Hidden Markov Models
and Linear Dynamic Models in a Hybrid Decoder Architecture for Continuous Speech
Recognition,” in Interspeech 2010, 2010.
mla: Leutnant, Volker, and Reinhold Haeb-Umbach. “On the Exploitation of Hidden
Markov Models and Linear Dynamic Models in a Hybrid Decoder Architecture for Continuous
Speech Recognition.” Interspeech 2010, 2010.
short: 'V. Leutnant, R. Haeb-Umbach, in: Interspeech 2010, 2010.'
date_created: 2019-07-12T05:29:37Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/LeHa10-2.pdf
oa: '1'
publication: Interspeech 2010
status: public
title: On the Exploitation of Hidden Markov Models and Linear Dynamic Models in a
Hybrid Decoder Architecture for Continuous Speech Recognition
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '11887'
abstract:
- lang: eng
text: We describe an algorithm that performs regularized non-negative matrix factorization
(NMF) to find independent components in non-negative data. Previous techniques
proposed for this purpose require the data to be grounded, with support that goes
down to 0 along each dimension. In our work, this requirement is eliminated. Based
on it, we present a technique to find a low-dimensional decomposition of spectrograms
by casting it as a problem of discovering independent non-negative components
from it. The algorithm itself is implemented as regularized non-negative matrix
factorization (NMF). Unlike other ICA algorithms, this algorithm computes the
mixing matrix rather than an unmixing matrix. This algorithm provides a better
decomposition than standard NMF when the underlying sources are independent. It
makes better use of additional observation streams than previous non-negative
ICA algorithms.
author:
- first_name: Bhiksha
full_name: Raj, Bhiksha
last_name: Raj
- first_name: Kevin W.
full_name: Wilson, Kevin W.
last_name: Wilson
- 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: 'Raj B, Wilson KW, Krueger A, Haeb-Umbach R. Ungrounded Independent Non-Negative
Factor Analysis. In: Interspeech 2010. ; 2010.'
apa: Raj, B., Wilson, K. W., Krueger, A., & Haeb-Umbach, R. (2010). Ungrounded
Independent Non-Negative Factor Analysis. In Interspeech 2010.
bibtex: '@inproceedings{Raj_Wilson_Krueger_Haeb-Umbach_2010, title={Ungrounded Independent
Non-Negative Factor Analysis}, booktitle={Interspeech 2010}, author={Raj, Bhiksha
and Wilson, Kevin W. and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2010}
}'
chicago: Raj, Bhiksha, Kevin W. Wilson, Alexander Krueger, and Reinhold Haeb-Umbach.
“Ungrounded Independent Non-Negative Factor Analysis.” In Interspeech 2010,
2010.
ieee: B. Raj, K. W. Wilson, A. Krueger, and R. Haeb-Umbach, “Ungrounded Independent
Non-Negative Factor Analysis,” in Interspeech 2010, 2010.
mla: Raj, Bhiksha, et al. “Ungrounded Independent Non-Negative Factor Analysis.”
Interspeech 2010, 2010.
short: 'B. Raj, K.W. Wilson, A. Krueger, R. Haeb-Umbach, in: Interspeech 2010, 2010.'
date_created: 2019-07-12T05:30:10Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/RaWiKrHa10.pdf
oa: '1'
publication: Interspeech 2010
status: public
title: Ungrounded Independent Non-Negative Factor Analysis
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '11912'
abstract:
- lang: eng
text: In this contribution we provide a unified treatment of blind source separation
(BSS) and noise suppression, two tasks which have traditionally been considered
different and for which quite different techniques have been developed. Exploiting
the sparseness of the sources in the short time frequency domain and using a probabilistic
model which accounts for the presence of additive noise and which captures the
spatial information of the multi-channel recording, a speech enhancement system
is developed which suppresses noise and simultaneously separates speakers in case
multiple speakers are active. Source activity estimation and model parameter estimation
form the E-step and the M-step of the Expectation Maximization algorithm, respectively.
Experimental results obtained on the dataset of the Signal Separation Evaluation
Campaign 2010 demonstrate the effectiveness of the proposed system.
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. An EM Approach to Integrated Multichannel Speech
Separation and Noise Suppression. In: International Workshop on Acoustic Echo
and Noise Control (IWAENC 2010). ; 2010.'
apa: Tran Vu, D. H., & Haeb-Umbach, R. (2010). An EM Approach to Integrated
Multichannel Speech Separation and Noise Suppression. In International Workshop
on Acoustic Echo and Noise Control (IWAENC 2010).
bibtex: '@inproceedings{Tran Vu_Haeb-Umbach_2010, title={An EM Approach to Integrated
Multichannel Speech Separation and Noise Suppression}, booktitle={International
Workshop on Acoustic Echo and Noise Control (IWAENC 2010)}, author={Tran Vu, Dang
Hai and Haeb-Umbach, Reinhold}, year={2010} }'
chicago: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “An EM Approach to Integrated
Multichannel Speech Separation and Noise Suppression.” In International Workshop
on Acoustic Echo and Noise Control (IWAENC 2010), 2010.
ieee: D. H. Tran Vu and R. Haeb-Umbach, “An EM Approach to Integrated Multichannel
Speech Separation and Noise Suppression,” in International Workshop on Acoustic
Echo and Noise Control (IWAENC 2010), 2010.
mla: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “An EM Approach to Integrated
Multichannel Speech Separation and Noise Suppression.” International Workshop
on Acoustic Echo and Noise Control (IWAENC 2010), 2010.
short: 'D.H. Tran Vu, R. Haeb-Umbach, in: International Workshop on Acoustic Echo
and Noise Control (IWAENC 2010), 2010.'
date_created: 2019-07-12T05:30:39Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-1.pdf
oa: '1'
publication: International Workshop on Acoustic Echo and Noise Control (IWAENC 2010)
status: public
title: An EM Approach to Integrated Multichannel Speech Separation and Noise Suppression
type: conference
user_id: '44006'
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: '11892'
abstract:
- lang: eng
text: For an environment to be perceived as being smart, contextual information
has to be gathered to adapt the system's behavior and its interface towards the
user. Being a rich source of context information speech can be acquired unobtrusively
by microphone arrays and then processed to extract information about the user
and his environment. In this paper, a system for joint temporal segmentation,
speaker localization, and identification is presented, which is supported by face
identification from video data obtained from a steerable camera. Special attention
is paid to latency aspects and online processing capabilities, as they are important
for the application under investigation, namely ambient communication. It describes
the vision of terminal-less, session-less and multi-modal telecommunication with
remote partners, where the user can move freely within his home while the communication
follows him. The speaker diarization serves as a context source, which has been
integrated in a service-oriented middleware architecture and provided to the application
to select the most appropriate I/O device and to steer the camera towards the
speaker during ambient communication.
author:
- 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: Schmalenstroeer J, Haeb-Umbach R. Online Diarization of Streaming Audio-Visual
Data for Smart Environments. IEEE Journal of Selected Topics in Signal Processing.
2010;4(5):845-856. doi:10.1109/JSTSP.2010.2050519
apa: Schmalenstroeer, J., & Haeb-Umbach, R. (2010). Online Diarization of Streaming
Audio-Visual Data for Smart Environments. IEEE Journal of Selected Topics in
Signal Processing, 4(5), 845–856. https://doi.org/10.1109/JSTSP.2010.2050519
bibtex: '@article{Schmalenstroeer_Haeb-Umbach_2010, title={Online Diarization of
Streaming Audio-Visual Data for Smart Environments}, volume={4}, DOI={10.1109/JSTSP.2010.2050519},
number={5}, journal={IEEE Journal of Selected Topics in Signal Processing}, author={Schmalenstroeer,
Joerg and Haeb-Umbach, Reinhold}, year={2010}, pages={845–856} }'
chicago: 'Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Online Diarization
of Streaming Audio-Visual Data for Smart Environments.” IEEE Journal of Selected
Topics in Signal Processing 4, no. 5 (2010): 845–56. https://doi.org/10.1109/JSTSP.2010.2050519.'
ieee: 'J. Schmalenstroeer and R. Haeb-Umbach, “Online Diarization of Streaming Audio-Visual
Data for Smart Environments,” IEEE Journal of Selected Topics in Signal Processing,
vol. 4, no. 5, pp. 845–856, 2010, doi: 10.1109/JSTSP.2010.2050519.'
mla: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Online Diarization of Streaming
Audio-Visual Data for Smart Environments.” IEEE Journal of Selected Topics
in Signal Processing, vol. 4, no. 5, 2010, pp. 845–56, doi:10.1109/JSTSP.2010.2050519.
short: J. Schmalenstroeer, R. Haeb-Umbach, IEEE Journal of Selected Topics in Signal
Processing 4 (2010) 845–856.
date_created: 2019-07-12T05:30:16Z
date_updated: 2023-10-26T08:10:18Z
department:
- _id: '54'
doi: 10.1109/JSTSP.2010.2050519
intvolume: ' 4'
issue: '5'
keyword:
- audio streaming
- audio visual data streaming
- context information speech
- face identification
- face recognition
- image segmentation
- middleware
- multimodal telecommunication
- online diarization
- service oriented middleware architecture
- sessionless telecommunication
- software architecture
- speaker identification
- speaker localization
- speaker recognition
- steerable camera
- telecommunication computing
- temporal segmentation
- terminal-less telecommunication
- video streaming
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/ScHa10.pdf
oa: '1'
page: 845-856
publication: IEEE Journal of Selected Topics in Signal Processing
quality_controlled: '1'
status: public
title: Online Diarization of Streaming Audio-Visual Data for Smart Environments
type: journal_article
user_id: '460'
volume: 4
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: '11725'
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. Eine Plattform fuer Mehrwertdienste
im Bereich Logistik - Drahtlose Fahrzeug- und Laderaumueberwachung fuer LKW mit
Hilfe einer Maut-On-Board Unit. In: DGON Navigationskonvent 2009. ; 2009.'
apa: Bevermeier, M., Peschke, S., & Haeb-Umbach, R. (2009). Eine Plattform fuer
Mehrwertdienste im Bereich Logistik - Drahtlose Fahrzeug- und Laderaumueberwachung
fuer LKW mit Hilfe einer Maut-On-Board Unit. In DGON Navigationskonvent 2009.
bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Eine Plattform
fuer Mehrwertdienste im Bereich Logistik - Drahtlose Fahrzeug- und Laderaumueberwachung
fuer LKW mit Hilfe einer Maut-On-Board Unit}, booktitle={DGON Navigationskonvent
2009}, author={Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold},
year={2009} }'
chicago: Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Eine Plattform
Fuer Mehrwertdienste Im Bereich Logistik - Drahtlose Fahrzeug- Und Laderaumueberwachung
Fuer LKW Mit Hilfe Einer Maut-On-Board Unit.” In DGON Navigationskonvent 2009,
2009.
ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Eine Plattform fuer Mehrwertdienste
im Bereich Logistik - Drahtlose Fahrzeug- und Laderaumueberwachung fuer LKW mit
Hilfe einer Maut-On-Board Unit,” in DGON Navigationskonvent 2009, 2009.
mla: Bevermeier, Maik, et al. “Eine Plattform Fuer Mehrwertdienste Im Bereich Logistik
- Drahtlose Fahrzeug- Und Laderaumueberwachung Fuer LKW Mit Hilfe Einer Maut-On-Board
Unit.” DGON Navigationskonvent 2009, 2009.
short: 'M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: DGON Navigationskonvent 2009,
2009.'
date_created: 2019-07-12T05:27:03Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09-2.pdf
oa: '1'
publication: DGON Navigationskonvent 2009
status: public
title: Eine Plattform fuer Mehrwertdienste im Bereich Logistik - Drahtlose Fahrzeug-
und Laderaumueberwachung fuer LKW mit Hilfe einer Maut-On-Board Unit
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11847'
abstract:
- lang: eng
text: In this paper we present a new feature space dereverberation technique for
automatic speech recognition. We derive an expression for the dependence of the
reverberant speech features in the log-mel spectral domain on the non-reverberant
speech features and the room impulse response. The obtained observation model
is used for a model based speech enhancement based on Kalman filtering. The performance
of the proposed enhancement technique is studied on the AURORA5 database. In our
currently best configuration, which includes uncertainty decoding, the number
of recognition errors is approximately halved compared to the recognition of unprocessed
speech.
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 automatic speech
recognition in reverberant environments. In: Interspeech 2009. ; 2009.'
apa: Krueger, A., & Haeb-Umbach, R. (2009). Model based feature enhancement
for automatic speech recognition in reverberant environments. In Interspeech
2009.
bibtex: '@inproceedings{Krueger_Haeb-Umbach_2009, title={Model based feature enhancement
for automatic speech recognition in reverberant environments}, booktitle={Interspeech
2009}, author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2009} }'
chicago: Krueger, Alexander, and Reinhold Haeb-Umbach. “Model Based Feature Enhancement
for Automatic Speech Recognition in Reverberant Environments.” In Interspeech
2009, 2009.
ieee: A. Krueger and R. Haeb-Umbach, “Model based feature enhancement for automatic
speech recognition in reverberant environments,” in Interspeech 2009, 2009.
mla: Krueger, Alexander, and Reinhold Haeb-Umbach. “Model Based Feature Enhancement
for Automatic Speech Recognition in Reverberant Environments.” Interspeech
2009, 2009.
short: 'A. Krueger, R. Haeb-Umbach, in: Interspeech 2009, 2009.'
date_created: 2019-07-12T05:29:24Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/KrHa09.pdf
oa: '1'
publication: Interspeech 2009
status: public
title: Model based feature enhancement for automatic speech recognition in reverberant
environments
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11859'
abstract:
- lang: eng
text: In this paper we present an Uncertainty Decoding rule which exploits feature
reliability information and interframe correlation for noise robust speech recognition.
The reliability information can be obtained either from conditional Bayesian estimation,
where speech and noise feature vectors are tracked jointly, or by augmenting conventional
point estimation methods with heuristics about the estimator's reliability. Experimental
results on the AURORA2 database demonstrate on the one hand that Uncertainty Decoding
improves recognition performance, while on the other hand it is seen that the
severe approximations needed to arrive at computationally tractable solutions
have their noticable impact on recognition performance.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Leutnant V, Haeb-Umbach R. On the Estimation and Use of Feature Reliability
Information for Noise Robust Speech Recognition. In: International Conference
on Acoustics (NAG/DAGA 2009). ; 2009.'
apa: Leutnant, V., & Haeb-Umbach, R. (2009). On the Estimation and Use of Feature
Reliability Information for Noise Robust Speech Recognition. In International
Conference on Acoustics (NAG/DAGA 2009).
bibtex: '@inproceedings{Leutnant_Haeb-Umbach_2009, title={On the Estimation and
Use of Feature Reliability Information for Noise Robust Speech Recognition}, booktitle={International
Conference on Acoustics (NAG/DAGA 2009)}, author={Leutnant, Volker and Haeb-Umbach,
Reinhold}, year={2009} }'
chicago: Leutnant, Volker, and Reinhold Haeb-Umbach. “On the Estimation and Use
of Feature Reliability Information for Noise Robust Speech Recognition.” In International
Conference on Acoustics (NAG/DAGA 2009), 2009.
ieee: V. Leutnant and R. Haeb-Umbach, “On the Estimation and Use of Feature Reliability
Information for Noise Robust Speech Recognition,” in International Conference
on Acoustics (NAG/DAGA 2009), 2009.
mla: Leutnant, Volker, and Reinhold Haeb-Umbach. “On the Estimation and Use of Feature
Reliability Information for Noise Robust Speech Recognition.” International
Conference on Acoustics (NAG/DAGA 2009), 2009.
short: 'V. Leutnant, R. Haeb-Umbach, in: International Conference on Acoustics (NAG/DAGA
2009), 2009.'
date_created: 2019-07-12T05:29:38Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/LeHa09-1.pdf
oa: '1'
publication: International Conference on Acoustics (NAG/DAGA 2009)
status: public
title: On the Estimation and Use of Feature Reliability Information for Noise Robust
Speech Recognition
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11860'
abstract:
- lang: eng
text: In this paper we present an analytic derivation of the moments of the phase
factor between clean speech and noise cepstral or log-mel-spectral feature vectors.
The development shows, among others, that the probability density of the phase
factor is of sub-Gaussian nature and that it is independent of the noise type
and the signal-to-noise ratio, however dependent on the mel filter bank index.
Further we show how to compute the contribution of the phase factor to both the
mean and the vari- ance of the noisy speech observation likelihood, which relates
the speech and noise feature vectors to those of noisy speech. The resulting phase-sensitive
observation model is then used in model-based speech feature enhancement, leading
to significant improvements in word accuracy on the AURORA2 database.
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Leutnant V, Haeb-Umbach R. An analytic derivation of a phase-sensitive observation
model for noise robust speech recognition. In: Interspeech 2009. ; 2009.'
apa: Leutnant, V., & Haeb-Umbach, R. (2009). An analytic derivation of a phase-sensitive
observation model for noise robust speech recognition. In Interspeech 2009.
bibtex: '@inproceedings{Leutnant_Haeb-Umbach_2009, title={An analytic derivation
of a phase-sensitive observation model for noise robust speech recognition}, booktitle={Interspeech
2009}, author={Leutnant, Volker and Haeb-Umbach, Reinhold}, year={2009} }'
chicago: Leutnant, Volker, and Reinhold Haeb-Umbach. “An Analytic Derivation of
a Phase-Sensitive Observation Model for Noise Robust Speech Recognition.” In Interspeech
2009, 2009.
ieee: V. Leutnant and R. Haeb-Umbach, “An analytic derivation of a phase-sensitive
observation model for noise robust speech recognition,” in Interspeech 2009,
2009.
mla: Leutnant, Volker, and Reinhold Haeb-Umbach. “An Analytic Derivation of a Phase-Sensitive
Observation Model for Noise Robust Speech Recognition.” Interspeech 2009,
2009.
short: 'V. Leutnant, R. Haeb-Umbach, in: Interspeech 2009, 2009.'
date_created: 2019-07-12T05:29:39Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/LeHa09-2.pdf
oa: '1'
publication: Interspeech 2009
status: public
title: An analytic derivation of a phase-sensitive observation model for noise robust
speech recognition
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11881'
abstract:
- lang: eng
text: A combination of GPS (global positioning system) and INS (inertial navigation
system) is known to provide high precision and highly robust vehicle localization.
Notably during times when the GPS signal has a poor quality, e.g. due to the lack
of a sufficiently large number of visible satellites, the INS, which may consist
of a gyroscope and an odometer, will lead to improved positioning accuracy. In
this paper we show how velocity information obtained from GSM (global system for
mobile communications) signalling, rather than from a tachometer, can be used
together with a gyroscope sensor to support localization in the presence of temporarily
unavailable GPS data. We propose a sensor fusion system architecture and present
simulation results that show the effectiveness of this approach.
author:
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Peschke S, Bevermeier M, Haeb-Umbach R. A GPS positioning approach exploiting
GSM velocity estimates. In: 6th Workshop on Positioning Navigation and Communication
(WPNC 2009). ; 2009:195-202. doi:10.1109/WPNC.2009.4907827'
apa: Peschke, S., Bevermeier, M., & Haeb-Umbach, R. (2009). A GPS positioning
approach exploiting GSM velocity estimates. In 6th Workshop on Positioning
Navigation and Communication (WPNC 2009) (pp. 195–202). https://doi.org/10.1109/WPNC.2009.4907827
bibtex: '@inproceedings{Peschke_Bevermeier_Haeb-Umbach_2009, title={A GPS positioning
approach exploiting GSM velocity estimates}, DOI={10.1109/WPNC.2009.4907827},
booktitle={6th Workshop on Positioning Navigation and Communication (WPNC 2009)},
author={Peschke, Sven and Bevermeier, Maik and Haeb-Umbach, Reinhold}, year={2009},
pages={195–202} }'
chicago: Peschke, Sven, Maik Bevermeier, and Reinhold Haeb-Umbach. “A GPS Positioning
Approach Exploiting GSM Velocity Estimates.” In 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 195–202, 2009. https://doi.org/10.1109/WPNC.2009.4907827.
ieee: S. Peschke, M. Bevermeier, and R. Haeb-Umbach, “A GPS positioning approach
exploiting GSM velocity estimates,” in 6th Workshop on Positioning Navigation
and Communication (WPNC 2009), 2009, pp. 195–202.
mla: Peschke, Sven, et al. “A GPS Positioning Approach Exploiting GSM Velocity Estimates.”
6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009,
pp. 195–202, doi:10.1109/WPNC.2009.4907827.
short: 'S. Peschke, M. Bevermeier, R. Haeb-Umbach, in: 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 2009, pp. 195–202.'
date_created: 2019-07-12T05:30:04Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/WPNC.2009.4907827
keyword:
- cellular radio
- distance measurement
- global positioning system
- Global Positioning System
- global system for mobile communications
- GPS positioning approach
- GSM velocity
- gyroscopes
- gyroscope sensor
- inertial navigation
- inertial navigation system
- odometer
- sensor fusion system architecture
- sensors
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/PeBeHa09-1.pdf
oa: '1'
page: 195-202
publication: 6th Workshop on Positioning Navigation and Communication (WPNC 2009)
status: public
title: A GPS positioning approach exploiting GSM velocity estimates
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11882'
author:
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Peschke S, Bevermeier M, Haeb-Umbach R. Verbesserung von GPS-basierter Ortung
durch GSM-Geschwindigkeitsschaetzungen. In: DGON Navigationskonvent 2009.
; 2009.'
apa: Peschke, S., Bevermeier, M., & Haeb-Umbach, R. (2009). Verbesserung von
GPS-basierter Ortung durch GSM-Geschwindigkeitsschaetzungen. In DGON Navigationskonvent
2009.
bibtex: '@inproceedings{Peschke_Bevermeier_Haeb-Umbach_2009, title={Verbesserung
von GPS-basierter Ortung durch GSM-Geschwindigkeitsschaetzungen}, booktitle={DGON
Navigationskonvent 2009}, author={Peschke, Sven and Bevermeier, Maik and Haeb-Umbach,
Reinhold}, year={2009} }'
chicago: Peschke, Sven, Maik Bevermeier, and Reinhold Haeb-Umbach. “Verbesserung
von GPS-Basierter Ortung Durch GSM-Geschwindigkeitsschaetzungen.” In DGON Navigationskonvent
2009, 2009.
ieee: S. Peschke, M. Bevermeier, and R. Haeb-Umbach, “Verbesserung von GPS-basierter
Ortung durch GSM-Geschwindigkeitsschaetzungen,” in DGON Navigationskonvent
2009, 2009.
mla: Peschke, Sven, et al. “Verbesserung von GPS-Basierter Ortung Durch GSM-Geschwindigkeitsschaetzungen.”
DGON Navigationskonvent 2009, 2009.
short: 'S. Peschke, M. Bevermeier, R. Haeb-Umbach, in: DGON Navigationskonvent 2009,
2009.'
date_created: 2019-07-12T05:30:05Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/PeBeHa09-2.pdf
oa: '1'
publication: DGON Navigationskonvent 2009
status: public
title: Verbesserung von GPS-basierter Ortung durch GSM-Geschwindigkeitsschaetzungen
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'
...
---
_id: '11900'
author:
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Schmalenstroeer J, Leutnant V, Haeb-Umbach R. Audio-Visual Data Processing
for Ambient Communication. In: 1st International Workshop on Distributed Computing
in Ambient Environments within 32nd Annual Conference on Artificial Intelligence.
; 2009.'
apa: Schmalenstroeer, J., Leutnant, V., & Haeb-Umbach, R. (2009). Audio-Visual
Data Processing for Ambient Communication. 1st International Workshop on Distributed
Computing in Ambient Environments within 32nd Annual Conference on Artificial
Intelligence.
bibtex: '@inproceedings{Schmalenstroeer_Leutnant_Haeb-Umbach_2009, title={Audio-Visual
Data Processing for Ambient Communication}, booktitle={1st International Workshop
on Distributed Computing in Ambient Environments within 32nd Annual Conference
on Artificial Intelligence}, author={Schmalenstroeer, Joerg and Leutnant, Volker
and Haeb-Umbach, Reinhold}, year={2009} }'
chicago: Schmalenstroeer, Joerg, Volker Leutnant, and Reinhold Haeb-Umbach. “Audio-Visual
Data Processing for Ambient Communication.” In 1st International Workshop on
Distributed Computing in Ambient Environments within 32nd Annual Conference on
Artificial Intelligence, 2009.
ieee: J. Schmalenstroeer, V. Leutnant, and R. Haeb-Umbach, “Audio-Visual Data Processing
for Ambient Communication,” 2009.
mla: Schmalenstroeer, Joerg, et al. “Audio-Visual Data Processing for Ambient Communication.”
1st International Workshop on Distributed Computing in Ambient Environments
within 32nd Annual Conference on Artificial Intelligence, 2009.
short: 'J. Schmalenstroeer, V. Leutnant, R. Haeb-Umbach, in: 1st International Workshop
on Distributed Computing in Ambient Environments within 32nd Annual Conference
on Artificial Intelligence, 2009.'
date_created: 2019-07-12T05:30:25Z
date_updated: 2023-11-15T15:03:08Z
ddc:
- '004'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: schmalen
date_created: 2023-11-15T15:02:34Z
date_updated: 2023-11-15T15:02:34Z
file_id: '48934'
file_name: SchLeuHae09.pdf
file_size: 98062
relation: main_file
file_date_updated: 2023-11-15T15:02:34Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
publication: 1st International Workshop on Distributed Computing in Ambient Environments
within 32nd Annual Conference on Artificial Intelligence
quality_controlled: '1'
status: public
title: Audio-Visual Data Processing for Ambient Communication
type: conference
user_id: '460'
year: '2009'
...