---
_id: '2200'
author:
- first_name: Tobias
  full_name: Kenter, Tobias
  id: '3145'
  last_name: Kenter
- first_name: Marco
  full_name: Platzner, Marco
  id: '398'
  last_name: Platzner
- first_name: Christian
  full_name: Plessl, Christian
  id: '16153'
  last_name: Plessl
  orcid: 0000-0001-5728-9982
- first_name: Michael
  full_name: Kauschke, Michael
  last_name: Kauschke
citation:
  ama: 'Kenter T, Platzner M, Plessl C, Kauschke M. Performance Estimation Framework
    for Automated Exploration of CPU-Accelerator Architectures. In: <i>Proc. Int.
    Symp. on Field-Programmable Gate Arrays (FPGA)</i>. ACM; 2011:177-180. doi:<a
    href="https://doi.org/10.1145/1950413.1950448">10.1145/1950413.1950448</a>'
  apa: Kenter, T., Platzner, M., Plessl, C., &#38; Kauschke, M. (2011). Performance
    Estimation Framework for Automated Exploration of CPU-Accelerator Architectures.
    <i>Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>, 177–180. <a
    href="https://doi.org/10.1145/1950413.1950448">https://doi.org/10.1145/1950413.1950448</a>
  bibtex: '@inproceedings{Kenter_Platzner_Plessl_Kauschke_2011, place={New York, NY,
    USA}, title={Performance Estimation Framework for Automated Exploration of CPU-Accelerator
    Architectures}, DOI={<a href="https://doi.org/10.1145/1950413.1950448">10.1145/1950413.1950448</a>},
    booktitle={Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)}, publisher={ACM},
    author={Kenter, Tobias and Platzner, Marco and Plessl, Christian and Kauschke,
    Michael}, year={2011}, pages={177–180} }'
  chicago: 'Kenter, Tobias, Marco Platzner, Christian Plessl, and Michael Kauschke.
    “Performance Estimation Framework for Automated Exploration of CPU-Accelerator
    Architectures.” In <i>Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>,
    177–80. New York, NY, USA: ACM, 2011. <a href="https://doi.org/10.1145/1950413.1950448">https://doi.org/10.1145/1950413.1950448</a>.'
  ieee: 'T. Kenter, M. Platzner, C. Plessl, and M. Kauschke, “Performance Estimation
    Framework for Automated Exploration of CPU-Accelerator Architectures,” in <i>Proc.
    Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>, 2011, pp. 177–180, doi:
    <a href="https://doi.org/10.1145/1950413.1950448">10.1145/1950413.1950448</a>.'
  mla: Kenter, Tobias, et al. “Performance Estimation Framework for Automated Exploration
    of CPU-Accelerator Architectures.” <i>Proc. Int. Symp. on Field-Programmable Gate
    Arrays (FPGA)</i>, ACM, 2011, pp. 177–80, doi:<a href="https://doi.org/10.1145/1950413.1950448">10.1145/1950413.1950448</a>.
  short: 'T. Kenter, M. Platzner, C. Plessl, M. Kauschke, in: Proc. Int. Symp. on
    Field-Programmable Gate Arrays (FPGA), ACM, New York, NY, USA, 2011, pp. 177–180.'
date_created: 2018-04-03T15:08:13Z
date_updated: 2023-09-26T13:45:04Z
department:
- _id: '27'
- _id: '518'
- _id: '78'
doi: 10.1145/1950413.1950448
keyword:
- design space exploration
- LLVM
- partitioning
- performance
- estimation
- funding-intel
language:
- iso: eng
page: 177-180
place: New York, NY, USA
publication: Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)
publication_identifier:
  isbn:
  - 978-1-4503-0554-9
publisher: ACM
quality_controlled: '1'
status: public
title: Performance Estimation Framework for Automated Exploration of CPU-Accelerator
  Architectures
type: conference
user_id: '15278'
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: <i>7th Workshop
    on Positioning Navigation and Communication (WPNC 2010)</i>. ; 2010:128-134. doi:<a
    href="https://doi.org/10.1109/WPNC.2010.5650745">10.1109/WPNC.2010.5650745</a>'
  apa: Bevermeier, M., Walter, O., Peschke, S., &#38; Haeb-Umbach, R. (2010). Barometric
    height estimation combined with map-matching in a loosely-coupled Kalman-filter.
    In <i>7th Workshop on Positioning Navigation and Communication (WPNC 2010)</i>
    (pp. 128–134). <a href="https://doi.org/10.1109/WPNC.2010.5650745">https://doi.org/10.1109/WPNC.2010.5650745</a>
  bibtex: '@inproceedings{Bevermeier_Walter_Peschke_Haeb-Umbach_2010, title={Barometric
    height estimation combined with map-matching in a loosely-coupled Kalman-filter},
    DOI={<a href="https://doi.org/10.1109/WPNC.2010.5650745">10.1109/WPNC.2010.5650745</a>},
    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 <i>7th Workshop on Positioning Navigation and Communication
    (WPNC 2010)</i>, 128–34, 2010. <a href="https://doi.org/10.1109/WPNC.2010.5650745">https://doi.org/10.1109/WPNC.2010.5650745</a>.
  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
    <i>7th Workshop on Positioning Navigation and Communication (WPNC 2010)</i>, 2010,
    pp. 128–134.
  mla: Bevermeier, Maik, et al. “Barometric Height Estimation Combined with Map-Matching
    in a Loosely-Coupled Kalman-Filter.” <i>7th Workshop on Positioning Navigation
    and Communication (WPNC 2010)</i>, 2010, pp. 128–34, doi:<a href="https://doi.org/10.1109/WPNC.2010.5650745">10.1109/WPNC.2010.5650745</a>.
  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. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>.
    2010;18(7):1692-1707. doi:<a href="https://doi.org/10.1109/TASL.2010.2049684">10.1109/TASL.2010.2049684</a>
  apa: Krueger, A., &#38; Haeb-Umbach, R. (2010). Model-Based Feature Enhancement
    for Reverberant Speech Recognition. <i>IEEE Transactions on Audio, Speech, and
    Language Processing</i>, <i>18</i>(7), 1692–1707. <a href="https://doi.org/10.1109/TASL.2010.2049684">https://doi.org/10.1109/TASL.2010.2049684</a>
  bibtex: '@article{Krueger_Haeb-Umbach_2010, title={Model-Based Feature Enhancement
    for Reverberant Speech Recognition}, volume={18}, DOI={<a href="https://doi.org/10.1109/TASL.2010.2049684">10.1109/TASL.2010.2049684</a>},
    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.” <i>IEEE Transactions on Audio, Speech, and
    Language Processing</i> 18, no. 7 (2010): 1692–1707. <a href="https://doi.org/10.1109/TASL.2010.2049684">https://doi.org/10.1109/TASL.2010.2049684</a>.'
  ieee: A. Krueger and R. Haeb-Umbach, “Model-Based Feature Enhancement for Reverberant
    Speech Recognition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>,
    vol. 18, no. 7, pp. 1692–1707, 2010.
  mla: Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement
    for Reverberant Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and
    Language Processing</i>, vol. 18, no. 7, 2010, pp. 1692–707, doi:<a href="https://doi.org/10.1109/TASL.2010.2049684">10.1109/TASL.2010.2049684</a>.
  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: '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: <i>6th Workshop
    on Positioning Navigation and Communication (WPNC 2009)</i>. ; 2009:235-242. doi:<a
    href="https://doi.org/10.1109/WPNC.2009.4907833">10.1109/WPNC.2009.4907833</a>'
  apa: Bevermeier, M., Peschke, S., &#38; Haeb-Umbach, R. (2009). Robust vehicle localization
    based on multi-level sensor fusion and online parameter estimation. In <i>6th
    Workshop on Positioning Navigation and Communication (WPNC 2009)</i> (pp. 235–242).
    <a href="https://doi.org/10.1109/WPNC.2009.4907833">https://doi.org/10.1109/WPNC.2009.4907833</a>
  bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Robust vehicle
    localization based on multi-level sensor fusion and online parameter estimation},
    DOI={<a href="https://doi.org/10.1109/WPNC.2009.4907833">10.1109/WPNC.2009.4907833</a>},
    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 <i>6th Workshop on Positioning Navigation and Communication (WPNC 2009)</i>,
    235–42, 2009. <a href="https://doi.org/10.1109/WPNC.2009.4907833">https://doi.org/10.1109/WPNC.2009.4907833</a>.
  ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Robust vehicle localization
    based on multi-level sensor fusion and online parameter estimation,” in <i>6th
    Workshop on Positioning Navigation and Communication (WPNC 2009)</i>, 2009, pp.
    235–242.
  mla: Bevermeier, Maik, et al. “Robust Vehicle Localization Based on Multi-Level
    Sensor Fusion and Online Parameter Estimation.” <i>6th Workshop on Positioning
    Navigation and Communication (WPNC 2009)</i>, 2009, pp. 235–42, doi:<a href="https://doi.org/10.1109/WPNC.2009.4907833">10.1109/WPNC.2009.4907833</a>.
  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: <i>IEEE 69th Vehicular
    Technology Conference (VTC 2009 Spring)</i>. ; 2009:1-5. doi:<a href="https://doi.org/10.1109/VETECS.2009.5073634">10.1109/VETECS.2009.5073634</a>'
  apa: Bevermeier, M., Peschke, S., &#38; Haeb-Umbach, R. (2009). Joint Parameter
    Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.
    In <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i> (pp. 1–5).
    <a href="https://doi.org/10.1109/VETECS.2009.5073634">https://doi.org/10.1109/VETECS.2009.5073634</a>
  bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Joint Parameter
    Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning},
    DOI={<a href="https://doi.org/10.1109/VETECS.2009.5073634">10.1109/VETECS.2009.5073634</a>},
    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 <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i>, 1–5, 2009.
    <a href="https://doi.org/10.1109/VETECS.2009.5073634">https://doi.org/10.1109/VETECS.2009.5073634</a>.
  ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Joint Parameter Estimation
    and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning,” in <i>IEEE
    69th Vehicular Technology Conference (VTC 2009 Spring)</i>, 2009, pp. 1–5.
  mla: Bevermeier, Maik, et al. “Joint Parameter Estimation and Tracking in a Multi-Stage
    Kalman Filter for Vehicle Positioning.” <i>IEEE 69th Vehicular Technology Conference
    (VTC 2009 Spring)</i>, 2009, pp. 1–5, doi:<a href="https://doi.org/10.1109/VETECS.2009.5073634">10.1109/VETECS.2009.5073634</a>.
  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. <i>IEEE Transactions on Audio, Speech, and Language
    Processing</i>. 2009;17(8):1577-1590. doi:<a href="https://doi.org/10.1109/TASL.2009.2023172">10.1109/TASL.2009.2023172</a>
  apa: Windmann, S., &#38; Haeb-Umbach, R. (2009). Parameter Estimation of a State-Space
    Model of Noise for Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech,
    and Language Processing</i>, <i>17</i>(8), 1577–1590. <a href="https://doi.org/10.1109/TASL.2009.2023172">https://doi.org/10.1109/TASL.2009.2023172</a>
  bibtex: '@article{Windmann_Haeb-Umbach_2009, title={Parameter Estimation of a State-Space
    Model of Noise for Robust Speech Recognition}, volume={17}, DOI={<a href="https://doi.org/10.1109/TASL.2009.2023172">10.1109/TASL.2009.2023172</a>},
    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.” <i>IEEE Transactions
    on Audio, Speech, and Language Processing</i> 17, no. 8 (2009): 1577–90. <a href="https://doi.org/10.1109/TASL.2009.2023172">https://doi.org/10.1109/TASL.2009.2023172</a>.'
  ieee: S. Windmann and R. Haeb-Umbach, “Parameter Estimation of a State-Space Model
    of Noise for Robust Speech Recognition,” <i>IEEE Transactions on Audio, Speech,
    and Language Processing</i>, 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.” <i>IEEE Transactions on Audio,
    Speech, and Language Processing</i>, vol. 17, no. 8, 2009, pp. 1577–90, doi:<a
    href="https://doi.org/10.1109/TASL.2009.2023172">10.1109/TASL.2009.2023172</a>.
  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: <i>IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2008)</i>. ; 2008:73-76. doi:<a href="https://doi.org/10.1109/ICASSP.2008.4517549">10.1109/ICASSP.2008.4517549</a>'
  apa: Warsitz, E., Krueger, A., &#38; Haeb-Umbach, R. (2008). Speech enhancement
    with a new generalized eigenvector blocking matrix for application in a generalized
    sidelobe canceller. In <i>IEEE International Conference on Acoustics, Speech and
    Signal Processing (ICASSP 2008)</i> (pp. 73–76). <a href="https://doi.org/10.1109/ICASSP.2008.4517549">https://doi.org/10.1109/ICASSP.2008.4517549</a>
  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={<a href="https://doi.org/10.1109/ICASSP.2008.4517549">10.1109/ICASSP.2008.4517549</a>},
    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 <i>IEEE International Conference on Acoustics, Speech
    and Signal Processing (ICASSP 2008)</i>, 73–76, 2008. <a href="https://doi.org/10.1109/ICASSP.2008.4517549">https://doi.org/10.1109/ICASSP.2008.4517549</a>.
  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 <i>IEEE International Conference on Acoustics, Speech and Signal
    Processing (ICASSP 2008)</i>, 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.” <i>IEEE
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>,
    2008, pp. 73–76, doi:<a href="https://doi.org/10.1109/ICASSP.2008.4517549">10.1109/ICASSP.2008.4517549</a>.
  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: <i>IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2007)</i>. Vol 3. ; 2007:III-277-III-280.
    doi:<a href="https://doi.org/10.1109/ICASSP.2007.366526">10.1109/ICASSP.2007.366526</a>'
  apa: Haeb-Umbach, R., &#38; Bevermeier, M. (2007). OFDM Channel Estimation Based
    on Combined Estimation in Time and Frequency Domain. In <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)</i> (Vol.
    3, pp. III-277-III–280). <a href="https://doi.org/10.1109/ICASSP.2007.366526">https://doi.org/10.1109/ICASSP.2007.366526</a>
  bibtex: '@inproceedings{Haeb-Umbach_Bevermeier_2007, title={OFDM Channel Estimation
    Based on Combined Estimation in Time and Frequency Domain}, volume={3}, DOI={<a
    href="https://doi.org/10.1109/ICASSP.2007.366526">10.1109/ICASSP.2007.366526</a>},
    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 <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)</i>, 3:III-277-III–280,
    2007. <a href="https://doi.org/10.1109/ICASSP.2007.366526">https://doi.org/10.1109/ICASSP.2007.366526</a>.
  ieee: R. Haeb-Umbach and M. Bevermeier, “OFDM Channel Estimation Based on Combined
    Estimation in Time and Frequency Domain,” in <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2007)</i>, 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.” <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2007)</i>, vol. 3, 2007, pp.
    III-277-III–280, doi:<a href="https://doi.org/10.1109/ICASSP.2007.366526">10.1109/ICASSP.2007.366526</a>.
  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: <i>4th Workshop on Positioning Navigation and Communication
    (WPNC 2007)</i>. ; 2007:217-222. doi:<a href="https://doi.org/10.1109/WPNC.2007.353637">10.1109/WPNC.2007.353637</a>'
  apa: Peschke, S., &#38; Haeb-Umbach, R. (2007). Velocity Estimation of Mobile Terminals
    by Exploiting GSM Downlink Signalling. In <i>4th Workshop on Positioning Navigation
    and Communication (WPNC 2007)</i> (pp. 217–222). <a href="https://doi.org/10.1109/WPNC.2007.353637">https://doi.org/10.1109/WPNC.2007.353637</a>
  bibtex: '@inproceedings{Peschke_Haeb-Umbach_2007, title={Velocity Estimation of
    Mobile Terminals by Exploiting GSM Downlink Signalling}, DOI={<a href="https://doi.org/10.1109/WPNC.2007.353637">10.1109/WPNC.2007.353637</a>},
    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 <i>4th Workshop on Positioning
    Navigation and Communication (WPNC 2007)</i>, 217–22, 2007. <a href="https://doi.org/10.1109/WPNC.2007.353637">https://doi.org/10.1109/WPNC.2007.353637</a>.
  ieee: S. Peschke and R. Haeb-Umbach, “Velocity Estimation of Mobile Terminals by
    Exploiting GSM Downlink Signalling,” in <i>4th Workshop on Positioning Navigation
    and Communication (WPNC 2007)</i>, 2007, pp. 217–222.
  mla: Peschke, Sven, and Reinhold Haeb-Umbach. “Velocity Estimation of Mobile Terminals
    by Exploiting GSM Downlink Signalling.” <i>4th Workshop on Positioning Navigation
    and Communication (WPNC 2007)</i>, 2007, pp. 217–22, doi:<a href="https://doi.org/10.1109/WPNC.2007.353637">10.1109/WPNC.2007.353637</a>.
  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. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>.
    2007;15(5):1529-1539. doi:<a href="https://doi.org/10.1109/TASL.2007.898454">10.1109/TASL.2007.898454</a>
  apa: Warsitz, E., &#38; Haeb-Umbach, R. (2007). Blind Acoustic Beamforming Based
    on Generalized Eigenvalue Decomposition. <i>IEEE Transactions on Audio, Speech,
    and Language Processing</i>, <i>15</i>(5), 1529–1539. <a href="https://doi.org/10.1109/TASL.2007.898454">https://doi.org/10.1109/TASL.2007.898454</a>
  bibtex: '@article{Warsitz_Haeb-Umbach_2007, title={Blind Acoustic Beamforming Based
    on Generalized Eigenvalue Decomposition}, volume={15}, DOI={<a href="https://doi.org/10.1109/TASL.2007.898454">10.1109/TASL.2007.898454</a>},
    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.” <i>IEEE Transactions on Audio,
    Speech, and Language Processing</i> 15, no. 5 (2007): 1529–39. <a href="https://doi.org/10.1109/TASL.2007.898454">https://doi.org/10.1109/TASL.2007.898454</a>.'
  ieee: E. Warsitz and R. Haeb-Umbach, “Blind Acoustic Beamforming Based on Generalized
    Eigenvalue Decomposition,” <i>IEEE Transactions on Audio, Speech, and Language
    Processing</i>, vol. 15, no. 5, pp. 1529–1539, 2007.
  mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming Based
    on Generalized Eigenvalue Decomposition.” <i>IEEE Transactions on Audio, Speech,
    and Language Processing</i>, vol. 15, no. 5, 2007, pp. 1529–39, doi:<a href="https://doi.org/10.1109/TASL.2007.898454">10.1109/TASL.2007.898454</a>.
  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: <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>. Vol 1. ; 2006:I.
    doi:<a href="https://doi.org/10.1109/ICASSP.2006.1659984">10.1109/ICASSP.2006.1659984</a>'
  apa: Ion, V., &#38; Haeb-Umbach, R. (2006). An Inexpensive Packet Loss Compensation
    Scheme for Distributed Speech Recognition Based on Soft-Features. In <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i> (Vol.
    1, p. I). <a href="https://doi.org/10.1109/ICASSP.2006.1659984">https://doi.org/10.1109/ICASSP.2006.1659984</a>
  bibtex: '@inproceedings{Ion_Haeb-Umbach_2006, title={An Inexpensive Packet Loss
    Compensation Scheme for Distributed Speech Recognition Based on Soft-Features},
    volume={1}, DOI={<a href="https://doi.org/10.1109/ICASSP.2006.1659984">10.1109/ICASSP.2006.1659984</a>},
    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 <i>IEEE
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>,
    1:I, 2006. <a href="https://doi.org/10.1109/ICASSP.2006.1659984">https://doi.org/10.1109/ICASSP.2006.1659984</a>.
  ieee: V. Ion and R. Haeb-Umbach, “An Inexpensive Packet Loss Compensation Scheme
    for Distributed Speech Recognition Based on Soft-Features,” in <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, 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.” <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, vol.
    1, 2006, p. I, doi:<a href="https://doi.org/10.1109/ICASSP.2006.1659984">10.1109/ICASSP.2006.1659984</a>.
  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: <i>IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2005)</i>. Vol 4. ; 2005:iv/797-iv/800 Vol.
    4. doi:<a href="https://doi.org/10.1109/ICASSP.2005.1416129">10.1109/ICASSP.2005.1416129</a>'
  apa: Warsitz, E., &#38; Haeb-Umbach, R. (2005). Acoustic filter-and-sum beamforming
    by adaptive principal component analysis. In <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2005)</i> (Vol. 4, p. iv/797-iv/800
    Vol. 4). <a href="https://doi.org/10.1109/ICASSP.2005.1416129">https://doi.org/10.1109/ICASSP.2005.1416129</a>
  bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2005, title={Acoustic filter-and-sum
    beamforming by adaptive principal component analysis}, volume={4}, DOI={<a href="https://doi.org/10.1109/ICASSP.2005.1416129">10.1109/ICASSP.2005.1416129</a>},
    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 <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2005)</i>, 4:iv/797-iv/800
    Vol. 4, 2005. <a href="https://doi.org/10.1109/ICASSP.2005.1416129">https://doi.org/10.1109/ICASSP.2005.1416129</a>.
  ieee: E. Warsitz and R. Haeb-Umbach, “Acoustic filter-and-sum beamforming by adaptive
    principal component analysis,” in <i>IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2005)</i>, 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.” <i>IEEE International Conference on
    Acoustics, Speech and Signal Processing (ICASSP 2005)</i>, vol. 4, 2005, p. iv/797-iv/800
    Vol. 4, doi:<a href="https://doi.org/10.1109/ICASSP.2005.1416129">10.1109/ICASSP.2005.1416129</a>.
  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: <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>.
    ; 2004:367-370. doi:<a href="https://doi.org/10.1109/MMSP.2004.1436569">10.1109/MMSP.2004.1436569</a>'
  apa: Warsitz, E., &#38; Haeb-Umbach, R. (2004). Robust speaker direction estimation
    with particle filtering. In <i>IEEE Workshop on Multimedia Signal Processing (MMSP
    2004)</i> (pp. 367–370). <a href="https://doi.org/10.1109/MMSP.2004.1436569">https://doi.org/10.1109/MMSP.2004.1436569</a>
  bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2004, title={Robust speaker direction
    estimation with particle filtering}, DOI={<a href="https://doi.org/10.1109/MMSP.2004.1436569">10.1109/MMSP.2004.1436569</a>},
    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 <i>IEEE Workshop on Multimedia Signal Processing
    (MMSP 2004)</i>, 367–70, 2004. <a href="https://doi.org/10.1109/MMSP.2004.1436569">https://doi.org/10.1109/MMSP.2004.1436569</a>.
  ieee: E. Warsitz and R. Haeb-Umbach, “Robust speaker direction estimation with particle
    filtering,” in <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>,
    2004, pp. 367–370.
  mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation
    with Particle Filtering.” <i>IEEE Workshop on Multimedia Signal Processing (MMSP
    2004)</i>, 2004, pp. 367–70, doi:<a href="https://doi.org/10.1109/MMSP.2004.1436569">10.1109/MMSP.2004.1436569</a>.
  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. <i>IEEE Transactions on Speech and Audio Processing</i>. 2001;9(3):299-302.
    doi:<a href="https://doi.org/10.1109/89.906003">10.1109/89.906003</a>
  apa: Haeb-Umbach, R. (2001). Automatic generation of phonetic regression class trees
    for MLLR adaptation. <i>IEEE Transactions on Speech and Audio Processing</i>,
    <i>9</i>(3), 299–302. <a href="https://doi.org/10.1109/89.906003">https://doi.org/10.1109/89.906003</a>
  bibtex: '@article{Haeb-Umbach_2001, title={Automatic generation of phonetic regression
    class trees for MLLR adaptation}, volume={9}, DOI={<a href="https://doi.org/10.1109/89.906003">10.1109/89.906003</a>},
    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.” <i>IEEE Transactions on Speech and Audio Processing</i>
    9, no. 3 (2001): 299–302. <a href="https://doi.org/10.1109/89.906003">https://doi.org/10.1109/89.906003</a>.'
  ieee: R. Haeb-Umbach, “Automatic generation of phonetic regression class trees for
    MLLR adaptation,” <i>IEEE Transactions on Speech and Audio Processing</i>, vol.
    9, no. 3, pp. 299–302, 2001.
  mla: Haeb-Umbach, Reinhold. “Automatic Generation of Phonetic Regression Class Trees
    for MLLR Adaptation.” <i>IEEE Transactions on Speech and Audio Processing</i>,
    vol. 9, no. 3, 2001, pp. 299–302, doi:<a href="https://doi.org/10.1109/89.906003">10.1109/89.906003</a>.
  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'
...