---
_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: '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: '11935'
abstract:
- lang: eng
text: The generalized sidelobe canceller by Griffith and Jim is a robust beamforming
method to enhance a desired (speech) signal in the presence of stationary noise.
Its performance depends to a high degree on the construction of the blocking matrix
which produces noise reference signals for the subsequent adaptive interference
canceller. Especially in reverberated environments the beamformer may suffer from
signal leakage and reduced noise suppression. In this paper a new blocking matrix
is proposed. It is based on a generalized eigenvalue problem whose solution provides
an indirect estimation of the transfer functions from the source to the sensors.
The quality of the new generalized eigenvector blocking matrix is studied in simulated
rooms with different reverberation times and is compared to alternatives proposed
in the literature.
author:
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Warsitz E, Krueger A, Haeb-Umbach R. Speech enhancement with a new generalized
eigenvector blocking matrix for application in a generalized sidelobe canceller.
In: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008). ; 2008:73-76. doi:10.1109/ICASSP.2008.4517549'
apa: Warsitz, E., Krueger, A., & Haeb-Umbach, R. (2008). Speech enhancement
with a new generalized eigenvector blocking matrix for application in a generalized
sidelobe canceller. In IEEE International Conference on Acoustics, Speech and
Signal Processing (ICASSP 2008) (pp. 73–76). https://doi.org/10.1109/ICASSP.2008.4517549
bibtex: '@inproceedings{Warsitz_Krueger_Haeb-Umbach_2008, title={Speech enhancement
with a new generalized eigenvector blocking matrix for application in a generalized
sidelobe canceller}, DOI={10.1109/ICASSP.2008.4517549},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008)}, author={Warsitz, Ernst and Krueger, Alexander and Haeb-Umbach,
Reinhold}, year={2008}, pages={73–76} }'
chicago: Warsitz, Ernst, Alexander Krueger, and Reinhold Haeb-Umbach. “Speech Enhancement
with a New Generalized Eigenvector Blocking Matrix for Application in a Generalized
Sidelobe Canceller.” In IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP 2008), 73–76, 2008. https://doi.org/10.1109/ICASSP.2008.4517549.
ieee: E. Warsitz, A. Krueger, and R. Haeb-Umbach, “Speech enhancement with a new
generalized eigenvector blocking matrix for application in a generalized sidelobe
canceller,” in IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP 2008), 2008, pp. 73–76.
mla: Warsitz, Ernst, et al. “Speech Enhancement with a New Generalized Eigenvector
Blocking Matrix for Application in a Generalized Sidelobe Canceller.” IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008),
2008, pp. 73–76, doi:10.1109/ICASSP.2008.4517549.
short: 'E. Warsitz, A. Krueger, R. Haeb-Umbach, in: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 73–76.'
date_created: 2019-07-12T05:31:06Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2008.4517549
keyword:
- adaptive interference canceller
- adaptive signal processing
- array signal processing
- beamforming method
- eigenvalues and eigenfunctions
- generalized eigenvector blocking matrix
- generalized sidelobe canceller
- interference suppression
- matrix algebra
- noise suppression
- speech enhancement
- transfer function estimation
- transfer functions
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2008/WaKrHa08.pdf
oa: '1'
page: 73-76
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2008)
status: public
title: Speech enhancement with a new generalized eigenvector blocking matrix for application
in a generalized sidelobe canceller
type: conference
user_id: '44006'
year: '2008'
...
---
_id: '11785'
abstract:
- lang: eng
text: 'In this paper we present a novel channel impulse response estimation technique
for block-oriented OFDM transmission based on combining estimators: the estimates
provided by a Kalman filter operating in the time domain and a Wiener filter in
the frequency domain are optimally combined by taking into account their estimated
error covariances. The resulting estimator turns out to be identical to the MAP
estimator of correlated jointly Gaussian mean vectors. Different variants of the
proposed scheme are experimentally investigated in an EEEE 802.11a-like system
setup. They compare favourably with known approaches from the literature resulting
in reduced mean square estimation error and bit error rate. Further, robustness
and complexity issues are discussed'
author:
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
citation:
ama: 'Haeb-Umbach R, Bevermeier M. OFDM Channel Estimation Based on Combined Estimation
in Time and Frequency Domain. In: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2007). Vol 3. ; 2007:III-277-III-280.
doi:10.1109/ICASSP.2007.366526'
apa: Haeb-Umbach, R., & Bevermeier, M. (2007). OFDM Channel Estimation Based
on Combined Estimation in Time and Frequency Domain. In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2007) (Vol.
3, pp. III-277-III–280). https://doi.org/10.1109/ICASSP.2007.366526
bibtex: '@inproceedings{Haeb-Umbach_Bevermeier_2007, title={OFDM Channel Estimation
Based on Combined Estimation in Time and Frequency Domain}, volume={3}, DOI={10.1109/ICASSP.2007.366526},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2007)}, author={Haeb-Umbach, Reinhold and Bevermeier, Maik}, year={2007},
pages={III-277-III–280} }'
chicago: Haeb-Umbach, Reinhold, and Maik Bevermeier. “OFDM Channel Estimation Based
on Combined Estimation in Time and Frequency Domain.” In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2007), 3:III-277-III–280,
2007. https://doi.org/10.1109/ICASSP.2007.366526.
ieee: R. Haeb-Umbach and M. Bevermeier, “OFDM Channel Estimation Based on Combined
Estimation in Time and Frequency Domain,” in IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2007), 2007, vol. 3, pp.
III-277-III–280.
mla: Haeb-Umbach, Reinhold, and Maik Bevermeier. “OFDM Channel Estimation Based
on Combined Estimation in Time and Frequency Domain.” IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2007), vol. 3, 2007, pp.
III-277-III–280, doi:10.1109/ICASSP.2007.366526.
short: 'R. Haeb-Umbach, M. Bevermeier, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2007), 2007, pp. III-277-III–280.'
date_created: 2019-07-12T05:28:13Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2007.366526
intvolume: ' 3'
keyword:
- bit error rate
- block-oriented OFDM transmission
- channel estimation
- channel impulse response estimation
- combining estimators
- error statistics
- frequency domain estimation
- Gaussian mean vectors
- Gaussian processes
- Kalman filter
- Kalman filters
- MAP estimator
- maximum likelihood estimation
- OFDM channel estimation
- OFDM modulation
- time domain estimation
- time-frequency analysis
- Wiener filter
- Wiener filters
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2007/HaBe07.pdf
oa: '1'
page: III-277-III-280
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2007)
status: public
title: OFDM Channel Estimation Based on Combined Estimation in Time and Frequency
Domain
type: conference
user_id: '44006'
volume: 3
year: '2007'
...
---
_id: '11883'
abstract:
- lang: eng
text: In this paper, we experimentally evaluate algorithms for velocity estimation
of a GSM 900 mobile terminal which are based on the analysis of the statistical
properties of the fast fading process. It is shown how theses statistics can be
obtained from the training sequences present in downlink transmission bursts without
establishing an active connection. Realistic simulations of a GSM channel according
to the COST 207 channel models have been conducted. These models incorporate effects
like multipath propagation, fading, cochannel interference and additive noise.
It is shown that velocity estimation by searching for the maximum slope of the
power density spectrum of the fast fading performs best.
author:
- 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: 'Peschke S, Haeb-Umbach R. Velocity Estimation of Mobile Terminals by Exploiting
GSM Downlink Signalling. In: 4th Workshop on Positioning Navigation and Communication
(WPNC 2007). ; 2007:217-222. doi:10.1109/WPNC.2007.353637'
apa: Peschke, S., & Haeb-Umbach, R. (2007). Velocity Estimation of Mobile Terminals
by Exploiting GSM Downlink Signalling. In 4th Workshop on Positioning Navigation
and Communication (WPNC 2007) (pp. 217–222). https://doi.org/10.1109/WPNC.2007.353637
bibtex: '@inproceedings{Peschke_Haeb-Umbach_2007, title={Velocity Estimation of
Mobile Terminals by Exploiting GSM Downlink Signalling}, DOI={10.1109/WPNC.2007.353637},
booktitle={4th Workshop on Positioning Navigation and Communication (WPNC 2007)},
author={Peschke, Sven and Haeb-Umbach, Reinhold}, year={2007}, pages={217–222}
}'
chicago: Peschke, Sven, and Reinhold Haeb-Umbach. “Velocity Estimation of Mobile
Terminals by Exploiting GSM Downlink Signalling.” In 4th Workshop on Positioning
Navigation and Communication (WPNC 2007), 217–22, 2007. https://doi.org/10.1109/WPNC.2007.353637.
ieee: S. Peschke and R. Haeb-Umbach, “Velocity Estimation of Mobile Terminals by
Exploiting GSM Downlink Signalling,” in 4th Workshop on Positioning Navigation
and Communication (WPNC 2007), 2007, pp. 217–222.
mla: Peschke, Sven, and Reinhold Haeb-Umbach. “Velocity Estimation of Mobile Terminals
by Exploiting GSM Downlink Signalling.” 4th Workshop on Positioning Navigation
and Communication (WPNC 2007), 2007, pp. 217–22, doi:10.1109/WPNC.2007.353637.
short: 'S. Peschke, R. Haeb-Umbach, in: 4th Workshop on Positioning Navigation and
Communication (WPNC 2007), 2007, pp. 217–222.'
date_created: 2019-07-12T05:30:06Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/WPNC.2007.353637
keyword:
- additive noise
- cellular radio
- channel estimation
- cochannel interference
- COST 207 channel models
- downlink transmission bursts
- fading channels
- fading process
- GSM downlink signalling
- mobile terminals
- multipath channels
- multipath propagation
- power density spectrum
- statistical analysis
- statistical properties
- telecommunication links
- telecommunication terminals
- velocity estimation
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2007/PeHa07.pdf
oa: '1'
page: 217-222
publication: 4th Workshop on Positioning Navigation and Communication (WPNC 2007)
status: public
title: Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling
type: conference
user_id: '44006'
year: '2007'
...
---
_id: '11927'
abstract:
- lang: eng
text: Maximizing the output signal-to-noise ratio (SNR) of a sensor array in the
presence of spatially colored noise leads to a generalized eigenvalue problem.
While this approach has extensively been employed in narrowband (antenna) array
beamforming, it is typically not used for broadband (microphone) array beamforming
due to the uncontrolled amount of speech distortion introduced by a narrowband
SNR criterion. In this paper, we show how the distortion of the desired signal
can be controlled by a single-channel post-filter, resulting in a performance
comparable to the generalized minimum variance distortionless response beamformer,
where arbitrary transfer functions relate the source and the microphones. Results
are given both for directional and diffuse noise. A novel gradient ascent adaptation
algorithm is presented, and its good convergence properties are experimentally
revealed by comparison with alternatives from the literature. A key feature of
the proposed beamformer is that it operates blindly, i.e., it neither requires
knowledge about the array geometry nor an explicit estimation of the transfer
functions from source to sensors or the direction-of-arrival.
author:
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Warsitz E, Haeb-Umbach R. Blind Acoustic Beamforming Based on Generalized Eigenvalue
Decomposition. IEEE Transactions on Audio, Speech, and Language Processing.
2007;15(5):1529-1539. doi:10.1109/TASL.2007.898454
apa: Warsitz, E., & Haeb-Umbach, R. (2007). Blind Acoustic Beamforming Based
on Generalized Eigenvalue Decomposition. IEEE Transactions on Audio, Speech,
and Language Processing, 15(5), 1529–1539. https://doi.org/10.1109/TASL.2007.898454
bibtex: '@article{Warsitz_Haeb-Umbach_2007, title={Blind Acoustic Beamforming Based
on Generalized Eigenvalue Decomposition}, volume={15}, DOI={10.1109/TASL.2007.898454},
number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2007}, pages={1529–1539}
}'
chicago: 'Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming
Based on Generalized Eigenvalue Decomposition.” IEEE Transactions on Audio,
Speech, and Language Processing 15, no. 5 (2007): 1529–39. https://doi.org/10.1109/TASL.2007.898454.'
ieee: E. Warsitz and R. Haeb-Umbach, “Blind Acoustic Beamforming Based on Generalized
Eigenvalue Decomposition,” IEEE Transactions on Audio, Speech, and Language
Processing, vol. 15, no. 5, pp. 1529–1539, 2007.
mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming Based
on Generalized Eigenvalue Decomposition.” IEEE Transactions on Audio, Speech,
and Language Processing, vol. 15, no. 5, 2007, pp. 1529–39, doi:10.1109/TASL.2007.898454.
short: E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 15 (2007) 1529–1539.
date_created: 2019-07-12T05:30:57Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/TASL.2007.898454
intvolume: ' 15'
issue: '5'
keyword:
- acoustic signal processing
- arbitrary transfer function
- array signal processing
- blind acoustic beamforming
- direction-of-arrival
- direction-of-arrival estimation
- eigenvalues and eigenfunctions
- generalized eigenvalue decomposition
- gradient ascent adaptation algorithm
- microphone arrays
- microphones
- narrowband array beamforming
- sensor array
- single-channel post-filter
- spatially colored noise
- transfer functions
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2007/WaHa07.pdf
oa: '1'
page: 1529-1539
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition
type: journal_article
user_id: '44006'
volume: 15
year: '2007'
...
---
_id: '11824'
abstract:
- lang: eng
text: Soft-feature based speech recognition, which is an example of uncertainty
decoding, has been proven to be a robust error mitigation method for distributed
speech recognition over wireless channels exhibiting bit errors. In this paper
we extend this concept to packet-oriented transmissions. The a posteriori probability
density function of the lost feature vector, given the closest received neighbours,
is computed. In the experiments, the nearest frame repetition, which is shown
to be equivalent to the MAP estimate, outperforms the MMSE estimate for long bursts.
Taking the variance into account at the speech recognition stage results in superior
performance compared to classical schemes using point estimates. A computationally
and memory efficient implementation of the proposed packet loss compensation scheme
based on table lookup is presented
author:
- first_name: Valentin
full_name: Ion, Valentin
last_name: Ion
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ion V, Haeb-Umbach R. An Inexpensive Packet Loss Compensation Scheme for Distributed
Speech Recognition Based on Soft-Features. In: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2006). Vol 1. ; 2006:I.
doi:10.1109/ICASSP.2006.1659984'
apa: Ion, V., & Haeb-Umbach, R. (2006). An Inexpensive Packet Loss Compensation
Scheme for Distributed Speech Recognition Based on Soft-Features. In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) (Vol.
1, p. I). https://doi.org/10.1109/ICASSP.2006.1659984
bibtex: '@inproceedings{Ion_Haeb-Umbach_2006, title={An Inexpensive Packet Loss
Compensation Scheme for Distributed Speech Recognition Based on Soft-Features},
volume={1}, DOI={10.1109/ICASSP.2006.1659984},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2006)}, author={Ion, Valentin and Haeb-Umbach, Reinhold}, year={2006},
pages={I} }'
chicago: Ion, Valentin, and Reinhold Haeb-Umbach. “An Inexpensive Packet Loss Compensation
Scheme for Distributed Speech Recognition Based on Soft-Features.” In IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006),
1:I, 2006. https://doi.org/10.1109/ICASSP.2006.1659984.
ieee: V. Ion and R. Haeb-Umbach, “An Inexpensive Packet Loss Compensation Scheme
for Distributed Speech Recognition Based on Soft-Features,” in IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), 2006,
vol. 1, p. I.
mla: Ion, Valentin, and Reinhold Haeb-Umbach. “An Inexpensive Packet Loss Compensation
Scheme for Distributed Speech Recognition Based on Soft-Features.” IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), vol.
1, 2006, p. I, doi:10.1109/ICASSP.2006.1659984.
short: 'V. Ion, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2006), 2006, p. I.'
date_created: 2019-07-12T05:28:58Z
date_updated: 2022-01-06T06:51:10Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2006.1659984
intvolume: ' 1'
keyword:
- distributed speech recognition
- least mean squares methods
- MAP estimate
- maximum likelihood estimation
- MMSE estimate
- packet loss compensation scheme
- packet switched communication
- posteriori probability density function
- robust error mitigation method
- soft-features
- speech recognition
- table lookup
- voice communication
- wireless channels
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2006/IoHa06-2.pdf
oa: '1'
page: I
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2006)
status: public
title: An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition
Based on Soft-Features
type: conference
user_id: '44006'
volume: 1
year: '2006'
...
---
_id: '11930'
abstract:
- lang: eng
text: For human-machine interfaces in distant-talking environments multichannel
signal processing is often employed to obtain an enhanced signal for subsequent
processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum
beamformer to adjust the coefficients of FIR filters to changing acoustic room
impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient
ascent algorithm are derived from a constrained optimization problem, which iteratively
estimates the eigenvector corresponding to the largest eigenvalue of the cross
power spectral density of the microphone signals. The method does not require
an explicit estimation of the speaker location. The experimental results show
fast adaptation and excellent robustness of the proposed algorithm.
author:
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Warsitz E, Haeb-Umbach R. Acoustic filter-and-sum beamforming by adaptive
principal component analysis. In: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2005). Vol 4. ; 2005:iv/797-iv/800 Vol.
4. doi:10.1109/ICASSP.2005.1416129'
apa: Warsitz, E., & Haeb-Umbach, R. (2005). Acoustic filter-and-sum beamforming
by adaptive principal component analysis. In IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2005) (Vol. 4, p. iv/797-iv/800
Vol. 4). https://doi.org/10.1109/ICASSP.2005.1416129
bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2005, title={Acoustic filter-and-sum
beamforming by adaptive principal component analysis}, volume={4}, DOI={10.1109/ICASSP.2005.1416129},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2005)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2005},
pages={iv/797-iv/800 Vol. 4} }'
chicago: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming
by Adaptive Principal Component Analysis.” In IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2005), 4:iv/797-iv/800
Vol. 4, 2005. https://doi.org/10.1109/ICASSP.2005.1416129.
ieee: E. Warsitz and R. Haeb-Umbach, “Acoustic filter-and-sum beamforming by adaptive
principal component analysis,” in IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2005), 2005, vol. 4, p. iv/797-iv/800
Vol. 4.
mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming
by Adaptive Principal Component Analysis.” IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP 2005), vol. 4, 2005, p. iv/797-iv/800
Vol. 4, doi:10.1109/ICASSP.2005.1416129.
short: 'E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2005), 2005, p. iv/797-iv/800 Vol. 4.'
date_created: 2019-07-12T05:31:00Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2005.1416129
intvolume: ' 4'
keyword:
- acoustic filter-and-sum beamforming
- acoustic room impulses
- acoustic signal processing
- adaptive principal component analysis
- adaptive signal processing
- architectural acoustics
- constrained optimization problem
- cross power spectral density
- deterministic algorithm
- deterministic algorithms
- distant-talking environments
- eigenvalues and eigenfunctions
- eigenvector
- enhanced signal
- filter-and-sum beamformer
- FIR filter coefficients
- FIR filter coefficients
- FIR filters
- gradient methods
- human-machine interfaces
- iterative estimation
- iterative methods
- largest eigenvalue
- microphone signals
- multichannel signal processing
- optimisation
- principal component analysis
- spectral analysis
- stochastic gradient ascent algorithm
- stochastic processes
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2005/WaHa05.pdf
oa: '1'
page: iv/797-iv/800 Vol. 4
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2005)
status: public
title: Acoustic filter-and-sum beamforming by adaptive principal component analysis
type: conference
user_id: '44006'
volume: 4
year: '2005'
...
---
_id: '11931'
abstract:
- lang: eng
text: The paper is concerned with binaural signal processing for a bimodal human-robot
interface with hearing and vision. The two microphone signals are processed to
obtain an enhanced single-channel input signal for the subsequent speech recognizer
and to localize the acoustic source, an important information for establishing
a natural human-robot communication. We utilize a robust adaptive algorithm for
filter-and-sum beamforming (FSB) and extract speaker direction information from
the resulting FIR filter coefficients. Further, particle filtering is applied
which conducts a nonlinear Bayesian tracking of speaker movement. Good location
accuracy can be achieved even in highly reverberant environments. The results
obtained outperform the conventional generalized cross correlation (GCC) method.
author:
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Warsitz E, Haeb-Umbach R. Robust speaker direction estimation with particle
filtering. In: IEEE Workshop on Multimedia Signal Processing (MMSP 2004).
; 2004:367-370. doi:10.1109/MMSP.2004.1436569'
apa: Warsitz, E., & Haeb-Umbach, R. (2004). Robust speaker direction estimation
with particle filtering. In IEEE Workshop on Multimedia Signal Processing (MMSP
2004) (pp. 367–370). https://doi.org/10.1109/MMSP.2004.1436569
bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2004, title={Robust speaker direction
estimation with particle filtering}, DOI={10.1109/MMSP.2004.1436569},
booktitle={IEEE Workshop on Multimedia Signal Processing (MMSP 2004)}, author={Warsitz,
Ernst and Haeb-Umbach, Reinhold}, year={2004}, pages={367–370} }'
chicago: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation
with Particle Filtering.” In IEEE Workshop on Multimedia Signal Processing
(MMSP 2004), 367–70, 2004. https://doi.org/10.1109/MMSP.2004.1436569.
ieee: E. Warsitz and R. Haeb-Umbach, “Robust speaker direction estimation with particle
filtering,” in IEEE Workshop on Multimedia Signal Processing (MMSP 2004),
2004, pp. 367–370.
mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation
with Particle Filtering.” IEEE Workshop on Multimedia Signal Processing (MMSP
2004), 2004, pp. 367–70, doi:10.1109/MMSP.2004.1436569.
short: 'E. Warsitz, R. Haeb-Umbach, in: IEEE Workshop on Multimedia Signal Processing
(MMSP 2004), 2004, pp. 367–370.'
date_created: 2019-07-12T05:31:01Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/MMSP.2004.1436569
keyword:
- bimodal human-robot interface
- binaural signal processing
- enhanced single-channel input signal
- filter-and-sum beamforming
- filtering theory
- FIR filter coefficient
- generalized cross correlation method
- microphones
- microphone signal
- nonlinear Bayesian tracking
- particle filtering
- robust adaptive algorithm
- robust speaker direction estimation
- signal processing
- speech enhancement
- speech recognition
- speech recognizer
- user interfaces
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2004/WaHa04.pdf
oa: '1'
page: 367-370
publication: IEEE Workshop on Multimedia Signal Processing (MMSP 2004)
status: public
title: Robust speaker direction estimation with particle filtering
type: conference
user_id: '44006'
year: '2004'
...
---
_id: '11778'
abstract:
- lang: eng
text: In this paper, it is shown that a correlation criterion is the appropriate
criterion for bottom-up clustering to obtain broad phonetic class regression trees
for maximum likelihood linear regression (MLLR)-based speaker adaptation. The
correlation structure among speech units is estimated on the speaker-independent
training data. In adaptation experiments the tree outperformed a regression tree
obtained from clustering according to closeness in acoustic space and achieved
results comparable with those of a manually designed broad phonetic class tree
author:
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Haeb-Umbach R. Automatic generation of phonetic regression class trees for
MLLR adaptation. IEEE Transactions on Speech and Audio Processing. 2001;9(3):299-302.
doi:10.1109/89.906003
apa: Haeb-Umbach, R. (2001). Automatic generation of phonetic regression class trees
for MLLR adaptation. IEEE Transactions on Speech and Audio Processing,
9(3), 299–302. https://doi.org/10.1109/89.906003
bibtex: '@article{Haeb-Umbach_2001, title={Automatic generation of phonetic regression
class trees for MLLR adaptation}, volume={9}, DOI={10.1109/89.906003},
number={3}, journal={IEEE Transactions on Speech and Audio Processing}, author={Haeb-Umbach,
Reinhold}, year={2001}, pages={299–302} }'
chicago: 'Haeb-Umbach, Reinhold. “Automatic Generation of Phonetic Regression Class
Trees for MLLR Adaptation.” IEEE Transactions on Speech and Audio Processing
9, no. 3 (2001): 299–302. https://doi.org/10.1109/89.906003.'
ieee: R. Haeb-Umbach, “Automatic generation of phonetic regression class trees for
MLLR adaptation,” IEEE Transactions on Speech and Audio Processing, vol.
9, no. 3, pp. 299–302, 2001.
mla: Haeb-Umbach, Reinhold. “Automatic Generation of Phonetic Regression Class Trees
for MLLR Adaptation.” IEEE Transactions on Speech and Audio Processing,
vol. 9, no. 3, 2001, pp. 299–302, doi:10.1109/89.906003.
short: R. Haeb-Umbach, IEEE Transactions on Speech and Audio Processing 9 (2001)
299–302.
date_created: 2019-07-12T05:28:04Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
doi: 10.1109/89.906003
intvolume: ' 9'
issue: '3'
keyword:
- acoustic space
- adaptation experiments
- automatic generation
- bottom-up clustering
- broad phonetic class regression trees
- correlation criterion
- correlation methods
- maximum likelihood estimation
- maximum likelihood linear regression based speaker adaptation
- MLLR adaptation
- pattern clustering
- phonetic regression class trees
- speaker-independent training data
- speech recognition
- speech units
- statistical analysis
- trees (mathematics)
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2001/Ha01.pdf
oa: '1'
page: 299-302
publication: IEEE Transactions on Speech and Audio Processing
status: public
title: Automatic generation of phonetic regression class trees for MLLR adaptation
type: journal_article
user_id: '44006'
volume: 9
year: '2001'
...