---
_id: '11876'
abstract:
- lang: eng
  text: This paper describes the systems for the single-array track and the multiple-array
    track of the 5th CHiME Challenge. The final system is a combination of multiple
    systems, using Confusion Network Combination (CNC). The different systems presented
    here are utilizing different front-ends and training sets for a Bidirectional
    Long Short-Term Memory (BLSTM) Acoustic Model (AM). The front-end was replaced
    by enhancements provided by Paderborn University [1]. The back-end has been implemented
    using RASR [2] and RETURNN [3]. Additionally, a system combination including the
    hypothesis word graphs from the system of the submission [1] has been performed,
    which results in the final best system.
author:
- first_name: Markus
  full_name: Kitza, Markus
  last_name: Kitza
- first_name: Wilfried
  full_name: Michel, Wilfried
  last_name: Michel
- first_name: Christoph
  full_name: Boeddeker, Christoph
  id: '40767'
  last_name: Boeddeker
- first_name: Jens
  full_name: Heitkaemper, Jens
  id: '27643'
  last_name: Heitkaemper
- first_name: Tobias
  full_name: Menne, Tobias
  last_name: Menne
- first_name: Ralf
  full_name: Schlüter, Ralf
  last_name: Schlüter
- first_name: Hermann
  full_name: Ney, Hermann
  last_name: Ney
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Jahn
  full_name: Heymann, Jahn
  id: '9168'
  last_name: Heymann
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Kitza M, Michel W, Boeddeker C, et al. The RWTH/UPB System Combination for
    the CHiME 2018 Workshop. In: <i>Proc. CHiME 2018 Workshop on Speech Processing
    in Everyday Environments, Hyderabad, India</i>. ; 2018.'
  apa: Kitza, M., Michel, W., Boeddeker, C., Heitkaemper, J., Menne, T., Schlüter,
    R., Ney, H., Schmalenstroeer, J., Drude, L., Heymann, J., &#38; Haeb-Umbach, R.
    (2018). The RWTH/UPB System Combination for the CHiME 2018 Workshop. <i>Proc.
    CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad,
    India</i>.
  bibtex: '@inproceedings{Kitza_Michel_Boeddeker_Heitkaemper_Menne_Schlüter_Ney_Schmalenstroeer_Drude_Heymann_et
    al._2018, title={The RWTH/UPB System Combination for the CHiME 2018 Workshop},
    booktitle={Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments,
    Hyderabad, India}, author={Kitza, Markus and Michel, Wilfried and Boeddeker, Christoph
    and Heitkaemper, Jens and Menne, Tobias and Schlüter, Ralf and Ney, Hermann and
    Schmalenstroeer, Joerg and Drude, Lukas and Heymann, Jahn and et al.}, year={2018}
    }'
  chicago: Kitza, Markus, Wilfried Michel, Christoph Boeddeker, Jens Heitkaemper,
    Tobias Menne, Ralf Schlüter, Hermann Ney, et al. “The RWTH/UPB System Combination
    for the CHiME 2018 Workshop.” In <i>Proc. CHiME 2018 Workshop on Speech Processing
    in Everyday Environments, Hyderabad, India</i>, 2018.
  ieee: M. Kitza <i>et al.</i>, “The RWTH/UPB System Combination for the CHiME 2018
    Workshop,” 2018.
  mla: Kitza, Markus, et al. “The RWTH/UPB System Combination for the CHiME 2018 Workshop.”
    <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad,
    India</i>, 2018.
  short: 'M. Kitza, W. Michel, C. Boeddeker, J. Heitkaemper, T. Menne, R. Schlüter,
    H. Ney, J. Schmalenstroeer, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc. CHiME
    2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India,
    2018.'
date_created: 2019-07-12T05:29:58Z
date_updated: 2023-10-26T08:12:14Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2018/INTERSPEECH_2018_Heitkaemper_RWTH_Paper.pdf
oa: '1'
publication: Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments,
  Hyderabad, India
quality_controlled: '1'
status: public
title: The RWTH/UPB System Combination for the CHiME 2018 Workshop
type: conference
user_id: '460'
year: '2018'
...
---
_id: '11836'
abstract:
- lang: eng
  text: Due to their distributed nature wireless acoustic sensor networks offer great
    potential for improved signal acquisition, processing and classification for applications
    such as monitoring and surveillance, home automation, or hands-free telecommunication.
    To reduce the communication demand with a central server and to raise the privacy
    level it is desirable to perform processing at node level. The limited processing
    and memory capabilities on a sensor node, however, stand in contrast to the compute
    and memory intensive deep learning algorithms used in modern speech and audio
    processing. In this work, we perform benchmarking of commonly used convolutional
    and recurrent neural network architectures on a Raspberry Pi based acoustic sensor
    node. We show that it is possible to run medium-sized neural network topologies
    used for speech enhancement and speech recognition in real time. For acoustic
    event recognition, where predictions in a lower temporal resolution are sufficient,
    it is even possible to run current state-of-the-art deep convolutional models
    with a real-time-factor of 0:11.
author:
- first_name: Janek
  full_name: Ebbers, Janek
  id: '34851'
  last_name: Ebbers
- first_name: Jens
  full_name: Heitkaemper, Jens
  id: '27643'
  last_name: Heitkaemper
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Ebbers J, Heitkaemper J, Schmalenstroeer J, Haeb-Umbach R. Benchmarking Neural
    Network Architectures for Acoustic Sensor Networks. In: <i>ITG 2018, Oldenburg,
    Germany</i>. ; 2018.'
  apa: Ebbers, J., Heitkaemper, J., Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2018).
    Benchmarking Neural Network Architectures for Acoustic Sensor Networks. <i>ITG
    2018, Oldenburg, Germany</i>.
  bibtex: '@inproceedings{Ebbers_Heitkaemper_Schmalenstroeer_Haeb-Umbach_2018, title={Benchmarking
    Neural Network Architectures for Acoustic Sensor Networks}, booktitle={ITG 2018,
    Oldenburg, Germany}, author={Ebbers, Janek and Heitkaemper, Jens and Schmalenstroeer,
    Joerg and Haeb-Umbach, Reinhold}, year={2018} }'
  chicago: Ebbers, Janek, Jens Heitkaemper, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach.
    “Benchmarking Neural Network Architectures for Acoustic Sensor Networks.” In <i>ITG
    2018, Oldenburg, Germany</i>, 2018.
  ieee: J. Ebbers, J. Heitkaemper, J. Schmalenstroeer, and R. Haeb-Umbach, “Benchmarking
    Neural Network Architectures for Acoustic Sensor Networks,” 2018.
  mla: Ebbers, Janek, et al. “Benchmarking Neural Network Architectures for Acoustic
    Sensor Networks.” <i>ITG 2018, Oldenburg, Germany</i>, 2018.
  short: 'J. Ebbers, J. Heitkaemper, J. Schmalenstroeer, R. Haeb-Umbach, in: ITG 2018,
    Oldenburg, Germany, 2018.'
date_created: 2019-07-12T05:29:11Z
date_updated: 2023-10-26T08:12:40Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Ebbers_Paper.pdf
oa: '1'
publication: ITG 2018, Oldenburg, Germany
quality_controlled: '1'
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Ebbers_Poster.pdf
status: public
title: Benchmarking Neural Network Architectures for Acoustic Sensor Networks
type: conference
user_id: '460'
year: '2018'
...
---
_id: '11839'
abstract:
- lang: eng
  text: It has been experimentally verified that sampling rate offsets (SROs) between
    the input channels of an acoustic beamformer have a detrimental effect on the
    achievable SNR gains. In this paper we derive an analytic model to study the impact
    of SRO on the estimation of the spatial noise covariance matrix used in MVDR beamforming.
    It is shown that a perfect compensation of the SRO is impossible if the noise
    covariance matrix is estimated by time averaging, even if the SRO is perfectly
    known. The SRO should therefore be compensated for prior to beamformer coefficient
    estimation. We present a novel scheme where SRO compensation and beamforming closely
    interact, saving some computational effort compared to separate SRO adjustment
    followed by acoustic beamforming.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Schmalenstroeer J, Haeb-Umbach R. Insights into the Interplay of Sampling
    Rate Offsets and MVDR Beamforming. In: <i>ITG 2018, Oldenburg, Germany</i>. ;
    2018.'
  apa: Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2018). Insights into the Interplay
    of Sampling Rate Offsets and MVDR Beamforming. <i>ITG 2018, Oldenburg, Germany</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Haeb-Umbach_2018, title={Insights into the
    Interplay of Sampling Rate Offsets and MVDR Beamforming}, booktitle={ITG 2018,
    Oldenburg, Germany}, author={Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold},
    year={2018} }'
  chicago: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Insights into the Interplay
    of Sampling Rate Offsets and MVDR Beamforming.” In <i>ITG 2018, Oldenburg, Germany</i>,
    2018.
  ieee: J. Schmalenstroeer and R. Haeb-Umbach, “Insights into the Interplay of Sampling
    Rate Offsets and MVDR Beamforming,” 2018.
  mla: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Insights into the Interplay
    of Sampling Rate Offsets and MVDR Beamforming.” <i>ITG 2018, Oldenburg, Germany</i>,
    2018.
  short: 'J. Schmalenstroeer, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.'
date_created: 2019-07-12T05:29:15Z
date_updated: 2023-10-26T08:12:22Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Schmalenstroeer_Paper.pdf
oa: '1'
publication: ITG 2018, Oldenburg, Germany
quality_controlled: '1'
status: public
title: Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming
type: conference
user_id: '460'
year: '2018'
...
---
_id: '15952'
abstract:
- lang: eng
  text: Arbitrary sampling rate conversion has already received considerable attention
    in the past, but still lacks an equivalent representation of the effective time-dilation
    process in the block frequency domain. Good sampling rate converters in the time
    domain have been known, for instance, in terms of time-varying 'Sinc' or fixed
    'Farrow' polynomial filters. The former can deliver nearly exact conversion at
    high complexity, while the latter has pronounced computational efficiency with
    limited accuracy. Only recently, it was shown that a composite 'polyphase Farrow'
    form with high resampling precision can be implemented with quasi-fixed filters
    that operate at the input sampling rate. We therefore propose to capitalize from
    that fixed-filter architecture in that we translate the polyphase-Farrow filters
    into an equivalent FFT-based overlap-save form. Experimental evaluation and comparison
    with other state-of-the art frequency-domain approaches then proves currently
    the best price-performance ratio of the proposed algorithm. It is thus an ideal
    candidate for the new framework of acoustic sensor networks that critically rests
    upon fast and accurate alignment of autonomous sampling processes.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Aleksej
  full_name: Chinaev, Aleksej
  last_name: Chinaev
- first_name: Gerald
  full_name: Enzner, Gerald
  last_name: Enzner
citation:
  ama: 'Schmalenstroeer J, Chinaev A, Enzner G. Fast and Accurate Audio Resampling
    for Acoustic Sensor Networks by Polyphase-Farrow Filters with FFT Realization.
    In: <i>Speech Communication; 13th ITG-Symposium</i>. ; 2018:1-5.'
  apa: Schmalenstroeer, J., Chinaev, A., &#38; Enzner, G. (2018). Fast and Accurate
    Audio Resampling for Acoustic Sensor Networks by Polyphase-Farrow Filters with
    FFT Realization. <i>Speech Communication; 13th ITG-Symposium</i>, 1–5.
  bibtex: '@inproceedings{Schmalenstroeer_Chinaev_Enzner_2018, title={Fast and Accurate
    Audio Resampling for Acoustic Sensor Networks by Polyphase-Farrow Filters with
    FFT Realization}, booktitle={Speech Communication; 13th ITG-Symposium}, author={Schmalenstroeer,
    Joerg and Chinaev, Aleksej and Enzner, Gerald}, year={2018}, pages={1–5} }'
  chicago: Schmalenstroeer, Joerg, Aleksej Chinaev, and Gerald Enzner. “Fast and Accurate
    Audio Resampling for Acoustic Sensor Networks by Polyphase-Farrow Filters with
    FFT Realization.” In <i>Speech Communication; 13th ITG-Symposium</i>, 1–5, 2018.
  ieee: J. Schmalenstroeer, A. Chinaev, and G. Enzner, “Fast and Accurate Audio Resampling
    for Acoustic Sensor Networks by Polyphase-Farrow Filters with FFT Realization,”
    in <i>Speech Communication; 13th ITG-Symposium</i>, 2018, pp. 1–5.
  mla: Schmalenstroeer, Joerg, et al. “Fast and Accurate Audio Resampling for Acoustic
    Sensor Networks by Polyphase-Farrow Filters with FFT Realization.” <i>Speech Communication;
    13th ITG-Symposium</i>, 2018, pp. 1–5.
  short: 'J. Schmalenstroeer, A. Chinaev, G. Enzner, in: Speech Communication; 13th
    ITG-Symposium, 2018, pp. 1–5.'
date_created: 2020-02-21T08:53:14Z
date_updated: 2024-11-14T09:42:35Z
department:
- _id: '54'
language:
- iso: eng
page: 1-5
project:
- _id: '52'
  name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Speech Communication; 13th ITG-Symposium
publication_identifier:
  issn:
  - 'null'
quality_controlled: '1'
status: public
title: Fast and Accurate Audio Resampling for Acoustic Sensor Networks by Polyphase-Farrow
  Filters with FFT Realization
type: conference
user_id: '460'
year: '2018'
...
---
_id: '12081'
abstract:
- lang: eng
  text: 'The invention relates to a building or enclosure termination opening and/or
    closing apparatus having communication signed or encrypted by means of a key,
    and to a method for operating such. To allow simple, convenient and secure use
    by exclusively authorised users, the apparatus comprises: a first and a second
    user terminal, with secure forwarding of a time-limited key from the first to
    the second user terminal being possible. According to an alternative, individual
    keys are generated by a user identification and a secret device key.'
author:
- first_name: Florian
  full_name: Jacob, Florian
  last_name: Jacob
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
citation:
  ama: Jacob F, Schmalenstroeer J. Building or Enclosure Termination Closing and/or
    Opening Apparatus, and Method for Operating a Building or Enclosure Termination.
    2017.
  apa: Jacob, F., &#38; Schmalenstroeer, J. (2017). Building or Enclosure Termination
    Closing and/or Opening Apparatus, and Method for Operating a Building or Enclosure
    Termination.
  bibtex: '@article{Jacob_Schmalenstroeer_2017, title={Building or Enclosure Termination
    Closing and/or Opening Apparatus, and Method for Operating a Building or Enclosure
    Termination}, author={Jacob, Florian and Schmalenstroeer, Joerg}, year={2017}
    }'
  chicago: Jacob, Florian, and Joerg Schmalenstroeer. “Building or Enclosure Termination
    Closing and/or Opening Apparatus, and Method for Operating a Building or Enclosure
    Termination,” 2017.
  ieee: F. Jacob and J. Schmalenstroeer, “Building or Enclosure Termination Closing
    and/or Opening Apparatus, and Method for Operating a Building or Enclosure Termination.”
    2017.
  mla: Jacob, Florian, and Joerg Schmalenstroeer. <i>Building or Enclosure Termination
    Closing and/or Opening Apparatus, and Method for Operating a Building or Enclosure
    Termination</i>. 2017.
  short: F. Jacob, J. Schmalenstroeer, (2017).
date_created: 2019-07-19T08:07:11Z
date_updated: 2022-01-06T06:51:17Z
department:
- _id: '54'
ipc: WO2018/077610A
ipn: WO2018/077610A
publication_date: '2017'
status: public
title: Building or Enclosure Termination Closing and/or Opening Apparatus, and Method
  for Operating a Building or Enclosure Termination
type: patent
user_id: '460'
year: '2017'
...
---
_id: '11895'
abstract:
- lang: eng
  text: Multi-channel speech enhancement algorithms rely on a synchronous sampling
    of the microphone signals. This, however, cannot always be guaranteed, especially
    if the sensors are distributed in an environment. To avoid performance degradation
    the sampling rate offset needs to be estimated and compensated for. In this contribution
    we extend the recently proposed coherence drift based method in two important
    directions. First, the increasing phase shift in the short-time Fourier transform
    domain is estimated from the coherence drift in a Matched Filterlike fashion,
    where intermediate estimates are weighted by their instantaneous SNR. Second,
    an observed bias is removed by iterating between offset estimation and compensation
    by resampling a couple of times. The effectiveness of the proposed method is demonstrated
    by speech recognition results on the output of a beamformer with and without sampling
    rate offset compensation between the input channels. We compare MVDR and maximum-SNR
    beamformers in reverberant environments and further show that both benefit from
    a novel phase normalization, which we also propose in this contribution.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Jahn
  full_name: Heymann, Jahn
  id: '9168'
  last_name: Heymann
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Christoph
  full_name: Boeddeker, Christoph
  id: '40767'
  last_name: Boeddeker
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Schmalenstroeer J, Heymann J, Drude L, Boeddeker C, Haeb-Umbach R. Multi-Stage
    Coherence Drift Based Sampling Rate Synchronization for Acoustic Beamforming.
    In: <i>IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)</i>.
    ; 2017.'
  apa: Schmalenstroeer, J., Heymann, J., Drude, L., Boeddeker, C., &#38; Haeb-Umbach,
    R. (2017). Multi-Stage Coherence Drift Based Sampling Rate Synchronization for
    Acoustic Beamforming. <i>IEEE 19th International Workshop on Multimedia Signal
    Processing (MMSP)</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Heymann_Drude_Boeddeker_Haeb-Umbach_2017,
    title={Multi-Stage Coherence Drift Based Sampling Rate Synchronization for Acoustic
    Beamforming}, booktitle={IEEE 19th International Workshop on Multimedia Signal
    Processing (MMSP)}, author={Schmalenstroeer, Joerg and Heymann, Jahn and Drude,
    Lukas and Boeddeker, Christoph and Haeb-Umbach, Reinhold}, year={2017} }'
  chicago: Schmalenstroeer, Joerg, Jahn Heymann, Lukas Drude, Christoph Boeddeker,
    and Reinhold Haeb-Umbach. “Multi-Stage Coherence Drift Based Sampling Rate Synchronization
    for Acoustic Beamforming.” In <i>IEEE 19th International Workshop on Multimedia
    Signal Processing (MMSP)</i>, 2017.
  ieee: J. Schmalenstroeer, J. Heymann, L. Drude, C. Boeddeker, and R. Haeb-Umbach,
    “Multi-Stage Coherence Drift Based Sampling Rate Synchronization for Acoustic
    Beamforming,” 2017.
  mla: Schmalenstroeer, Joerg, et al. “Multi-Stage Coherence Drift Based Sampling
    Rate Synchronization for Acoustic Beamforming.” <i>IEEE 19th International Workshop
    on Multimedia Signal Processing (MMSP)</i>, 2017.
  short: 'J. Schmalenstroeer, J. Heymann, L. Drude, C. Boeddeker, R. Haeb-Umbach,
    in: IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), 2017.'
date_created: 2019-07-12T05:30:20Z
date_updated: 2023-10-26T08:12:05Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2017/MMSP_2017_SchHaeb.pdf
oa: '1'
publication: IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)
quality_controlled: '1'
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2017/MMSP_2017_SchHaeb_poster.pdf
status: public
title: Multi-Stage Coherence Drift Based Sampling Rate Synchronization for Acoustic
  Beamforming
type: conference
user_id: '460'
year: '2017'
...
---
_id: '11890'
abstract:
- lang: eng
  text: In this paper we study the influence of directional radio patterns of Bluetooth
    low energy (BLE) beacons on smartphone localization accuracy and beacon network
    planning. A two-dimensional model of the power emission characteristic is derived
    from measurements of the radiation pattern of BLE beacons carried out in an RF
    chamber. The Cramer-Rao lower bound (CRLB) for position estimation is then derived
    for this directional power emission model. With this lower bound on the RMS positioning
    error the coverage of different beacon network configurations can be evaluated.
    For near-optimal network planing an evolutionary optimization algorithm for finding
    the best beacon placement is presented.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Schmalenstroeer J, Haeb-Umbach R. Investigations into Bluetooth Low Energy
    Localization Precision Limits. In: <i>24th European Signal Processing Conference
    (EUSIPCO 2016)</i>. ; 2016.'
  apa: Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2016). Investigations into Bluetooth
    Low Energy Localization Precision Limits. <i>24th European Signal Processing Conference
    (EUSIPCO 2016)</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Haeb-Umbach_2016, title={Investigations
    into Bluetooth Low Energy Localization Precision Limits}, booktitle={24th European
    Signal Processing Conference (EUSIPCO 2016)}, author={Schmalenstroeer, Joerg and
    Haeb-Umbach, Reinhold}, year={2016} }'
  chicago: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Investigations into
    Bluetooth Low Energy Localization Precision Limits.” In <i>24th European Signal
    Processing Conference (EUSIPCO 2016)</i>, 2016.
  ieee: J. Schmalenstroeer and R. Haeb-Umbach, “Investigations into Bluetooth Low
    Energy Localization Precision Limits,” 2016.
  mla: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Investigations into Bluetooth
    Low Energy Localization Precision Limits.” <i>24th European Signal Processing
    Conference (EUSIPCO 2016)</i>, 2016.
  short: 'J. Schmalenstroeer, R. Haeb-Umbach, in: 24th European Signal Processing
    Conference (EUSIPCO 2016), 2016.'
date_created: 2019-07-12T05:30:14Z
date_updated: 2023-10-26T08:11:52Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2016/SchHaeb16.pdf
oa: '1'
publication: 24th European Signal Processing Conference (EUSIPCO 2016)
quality_controlled: '1'
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2016/SchHaeb16_Poster.pdf
status: public
title: Investigations into Bluetooth Low Energy Localization Precision Limits
type: conference
user_id: '460'
year: '2016'
...
---
_id: '11874'
author:
- first_name: Manh Kha
  full_name: Hoang, Manh Kha
  last_name: Hoang
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Hoang MK, Schmalenstroeer J, Haeb-Umbach R. Aligning training models with
    smartphone properties in WiFi fingerprinting based indoor localization. In: <i>40th
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2015)</i>.
    ; 2015.'
  apa: Hoang, M. K., Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2015). Aligning training
    models with smartphone properties in WiFi fingerprinting based indoor localization.
    <i>40th International Conference on Acoustics, Speech and Signal Processing (ICASSP
    2015)</i>.
  bibtex: '@inproceedings{Hoang_Schmalenstroeer_Haeb-Umbach_2015, title={Aligning
    training models with smartphone properties in WiFi fingerprinting based indoor
    localization}, booktitle={40th International Conference on Acoustics, Speech and
    Signal Processing (ICASSP 2015)}, author={Hoang, Manh Kha and Schmalenstroeer,
    Joerg and Haeb-Umbach, Reinhold}, year={2015} }'
  chicago: Hoang, Manh Kha, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “Aligning
    Training Models with Smartphone Properties in WiFi Fingerprinting Based Indoor
    Localization.” In <i>40th International Conference on Acoustics, Speech and Signal
    Processing (ICASSP 2015)</i>, 2015.
  ieee: M. K. Hoang, J. Schmalenstroeer, and R. Haeb-Umbach, “Aligning training models
    with smartphone properties in WiFi fingerprinting based indoor localization,”
    2015.
  mla: Hoang, Manh Kha, et al. “Aligning Training Models with Smartphone Properties
    in WiFi Fingerprinting Based Indoor Localization.” <i>40th International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2015)</i>, 2015.
  short: 'M.K. Hoang, J. Schmalenstroeer, R. Haeb-Umbach, in: 40th International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2015), 2015.'
date_created: 2019-07-12T05:29:55Z
date_updated: 2023-10-26T08:11:43Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/HoSchHa2015.pdf
oa: '1'
publication: 40th International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2015)
quality_controlled: '1'
status: public
title: Aligning training models with smartphone properties in WiFi fingerprinting
  based indoor localization
type: conference
user_id: '460'
year: '2015'
...
---
_id: '11898'
abstract:
- lang: eng
  text: Abstract In this paper we present an approach for synchronizing a wireless
    acoustic sensor network using a two-stage procedure. First the clock frequency
    and phase differences between pairs of nodes are estimated employing a two-way
    message exchange protocol. The estimates are further improved in a Kalman filter
    with a dedicated observation error model. In the second stage network-wide synchronization
    is achieved by means of a gossiping algorithm which estimates the average clock
    frequency and phase of the sensor nodes. These averages are viewed as frequency
    and phase of a virtual master clock, to which the clocks of the sensor nodes have
    to be adjusted. The amount of adjustment is computed in a specific control loop.
    While these steps are done in software, the actual sampling rate correction is
    carried out in hardware by using an adjustable frequency synthesizer. Experimental
    results obtained from hardware devices and software simulations of large scale
    networks are presented.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Patrick
  full_name: Jebramcik, Patrick
  last_name: Jebramcik
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Schmalenstroeer J, Jebramcik P, Haeb-Umbach R. A combined hardware-software
    approach for acoustic sensor network synchronization . <i>Signal Processing</i>.
    2014;(0). doi:<a href="http://dx.doi.org/10.1016/j.sigpro.2014.06.030">http://dx.doi.org/10.1016/j.sigpro.2014.06.030</a>
  apa: Schmalenstroeer, J., Jebramcik, P., &#38; Haeb-Umbach, R. (2014). A combined
    hardware-software approach for acoustic sensor network synchronization . <i>Signal
    Processing</i>, <i>0</i>. <a href="http://dx.doi.org/10.1016/j.sigpro.2014.06.030">http://dx.doi.org/10.1016/j.sigpro.2014.06.030</a>
  bibtex: '@article{Schmalenstroeer_Jebramcik_Haeb-Umbach_2014, title={A combined
    hardware-software approach for acoustic sensor network synchronization }, DOI={<a
    href="http://dx.doi.org/10.1016/j.sigpro.2014.06.030">http://dx.doi.org/10.1016/j.sigpro.2014.06.030</a>},
    number={0}, journal={Signal Processing}, author={Schmalenstroeer, Joerg and Jebramcik,
    Patrick and Haeb-Umbach, Reinhold}, year={2014} }'
  chicago: Schmalenstroeer, Joerg, Patrick Jebramcik, and Reinhold Haeb-Umbach. “A
    Combined Hardware-Software Approach for Acoustic Sensor Network Synchronization
    .” <i>Signal Processing</i>, no. 0 (2014). <a href="http://dx.doi.org/10.1016/j.sigpro.2014.06.030">http://dx.doi.org/10.1016/j.sigpro.2014.06.030</a>.
  ieee: 'J. Schmalenstroeer, P. Jebramcik, and R. Haeb-Umbach, “A combined hardware-software
    approach for acoustic sensor network synchronization ,” <i>Signal Processing</i>,
    no. 0, p., 2014, doi: <a href="http://dx.doi.org/10.1016/j.sigpro.2014.06.030">http://dx.doi.org/10.1016/j.sigpro.2014.06.030</a>.'
  mla: Schmalenstroeer, Joerg, et al. “A Combined Hardware-Software Approach for Acoustic
    Sensor Network Synchronization .” <i>Signal Processing</i>, no. 0, 2014, p., doi:<a
    href="http://dx.doi.org/10.1016/j.sigpro.2014.06.030">http://dx.doi.org/10.1016/j.sigpro.2014.06.030</a>.
  short: J. Schmalenstroeer, P. Jebramcik, R. Haeb-Umbach, Signal Processing (2014).
date_created: 2019-07-12T05:30:23Z
date_updated: 2023-10-26T08:11:22Z
department:
- _id: '54'
doi: http://dx.doi.org/10.1016/j.sigpro.2014.06.030
issue: '0'
keyword:
- Gossip algorithm
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://www.sciencedirect.com/science/article/pii/S0165168414002990
oa: '1'
page: ' - '
publication: Signal Processing
publication_identifier:
  issn:
  - 0165-1684
quality_controlled: '1'
status: public
title: 'A combined hardware-software approach for acoustic sensor network synchronization '
type: journal_article
user_id: '460'
year: '2014'
...
---
_id: '11897'
abstract:
- lang: eng
  text: ' "In this paper we present an approach for synchronizing the sampling clocks
    of distributed microphones over a wireless network. The proposed system uses a
    two stage procedure. It first employs a two-way message exchange algorithm to
    estimate the clock phase and frequency difference between two nodes and then uses
    a gossiping algorithmto estimate a virtual master clock, to which all sensor nodes
    synchronize. Simulation results are presented for networks of different topology
    and size, showing the effectiveness of our approach." '
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Patrick
  full_name: Jebramcik, Patrick
  last_name: Jebramcik
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Schmalenstroeer J, Jebramcik P, Haeb-Umbach R. A Gossiping Approach to Sampling
    Clock Synchronization in Wireless Acoustic Sensor Networks. In: <i>39th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)</i>. ; 2014.'
  apa: Schmalenstroeer, J., Jebramcik, P., &#38; Haeb-Umbach, R. (2014). A Gossiping
    Approach to Sampling Clock Synchronization in Wireless Acoustic Sensor Networks.
    <i>39th International Conference on Acoustics, Speech and Signal Processing (ICASSP
    2014)</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Jebramcik_Haeb-Umbach_2014, title={A Gossiping
    Approach to Sampling Clock Synchronization in Wireless Acoustic Sensor Networks},
    booktitle={39th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2014)}, author={Schmalenstroeer, Joerg and Jebramcik, Patrick and Haeb-Umbach,
    Reinhold}, year={2014} }'
  chicago: Schmalenstroeer, Joerg, Patrick Jebramcik, and Reinhold Haeb-Umbach. “A
    Gossiping Approach to Sampling Clock Synchronization in Wireless Acoustic Sensor
    Networks.” In <i>39th International Conference on Acoustics, Speech and Signal
    Processing (ICASSP 2014)</i>, 2014.
  ieee: J. Schmalenstroeer, P. Jebramcik, and R. Haeb-Umbach, “A Gossiping Approach
    to Sampling Clock Synchronization in Wireless Acoustic Sensor Networks,” 2014.
  mla: Schmalenstroeer, Joerg, et al. “A Gossiping Approach to Sampling Clock Synchronization
    in Wireless Acoustic Sensor Networks.” <i>39th International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2014)</i>, 2014.
  short: 'J. Schmalenstroeer, P. Jebramcik, R. Haeb-Umbach, in: 39th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), 2014.'
date_created: 2019-07-12T05:30:22Z
date_updated: 2023-10-26T08:11:31Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2014/SchHae2014.pdf
oa: '1'
publication: 39th International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2014)
quality_controlled: '1'
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2014/SchHaebICASSP2014_Poster.pdf
status: public
title: A Gossiping Approach to Sampling Clock Synchronization in Wireless Acoustic
  Sensor Networks
type: conference
user_id: '460'
year: '2014'
...
---
_id: '11903'
abstract:
- lang: eng
  text: '"Acoustic sensor network clock synchronization via time stamp exchange between
    the sensor nodes is not accurate enough for many acoustic signal processing tasks,
    such as speaker localization. To improve synchronization accuracy it has therefore
    been proposed to employ a Kalman Filter to obtain improved frequency deviation
    and phase offset estimates. The estimation requires a statistical model of the
    errors of the measurements obtained from the time stamp exchange algorithm. These
    errors are caused by random transmission delays and hardware effects and are thus
    network specific. In this contribution we develop an algorithm to estimate the
    parameters of the measurement error model alongside the Kalman filter based sampling
    clock synchronization, employing the Expectation Maximization algorithm. Simulation
    results demonstrate that the online estimation of the error model parameters leads
    only to a small degradation of the synchronization performance compared to a perfectly
    known observation error model."'
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Weile
  full_name: Zhao, Weile
  last_name: Zhao
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Schmalenstroeer J, Zhao W, Haeb-Umbach R. Online Observation Error Model Estimation
    for Acoustic Sensor Network Synchronization. In: <i>11. ITG Fachtagung Sprachkommunikation
    (ITG 2014)</i>. ; 2014.'
  apa: Schmalenstroeer, J., Zhao, W., &#38; Haeb-Umbach, R. (2014). Online Observation
    Error Model Estimation for Acoustic Sensor Network Synchronization. <i>11. ITG
    Fachtagung Sprachkommunikation (ITG 2014)</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Zhao_Haeb-Umbach_2014, title={Online Observation
    Error Model Estimation for Acoustic Sensor Network Synchronization}, booktitle={11.
    ITG Fachtagung Sprachkommunikation (ITG 2014)}, author={Schmalenstroeer, Joerg
    and Zhao, Weile and Haeb-Umbach, Reinhold}, year={2014} }'
  chicago: Schmalenstroeer, Joerg, Weile Zhao, and Reinhold Haeb-Umbach. “Online Observation
    Error Model Estimation for Acoustic Sensor Network Synchronization.” In <i>11.
    ITG Fachtagung Sprachkommunikation (ITG 2014)</i>, 2014.
  ieee: J. Schmalenstroeer, W. Zhao, and R. Haeb-Umbach, “Online Observation Error
    Model Estimation for Acoustic Sensor Network Synchronization,” 2014.
  mla: Schmalenstroeer, Joerg, et al. “Online Observation Error Model Estimation for
    Acoustic Sensor Network Synchronization.” <i>11. ITG Fachtagung Sprachkommunikation
    (ITG 2014)</i>, 2014.
  short: 'J. Schmalenstroeer, W. Zhao, R. Haeb-Umbach, in: 11. ITG Fachtagung Sprachkommunikation
    (ITG 2014), 2014.'
date_created: 2019-07-12T05:30:29Z
date_updated: 2023-10-26T08:14:00Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2014/SchHaebITG2014.pdf
oa: '1'
publication: 11. ITG Fachtagung Sprachkommunikation (ITG 2014)
quality_controlled: '1'
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2014/SchHaebITG2014_Poster.pdf
  - description: Demo
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2014/SchHaebITG2014_Demo.pdf
status: public
title: Online Observation Error Model Estimation for Acoustic Sensor Network Synchronization
type: conference
user_id: '460'
year: '2014'
...
---
_id: '11926'
abstract:
- lang: eng
  text: In this paper we present a novel initialization method for unsupervised learning
    of acoustic patterns in recordings of continuous speech. The pattern discovery
    task is solved by dynamic time warping whose performance we improve by a smart
    starting point selection. This enables a more accurate discovery of patterns compared
    to conventional approaches. After graph-based clustering the patterns are employed
    for training hidden Markov models for an unsupervised speech acquisition. By iterating
    between model training and decoding in an EM-like framework the word accuracy
    is continuously improved. On the TIDIGITS corpus we achieve a word error rate
    of about 13 percent by the proposed unsupervised pattern discovery approach, which
    neither assumes knowledge of the acoustic units nor of the labels of the training
    data.
author:
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Walter O, Schmalenstroeer J, Haeb-Umbach R. <i>A Novel Initialization Method
    for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>.;
    2013.
  apa: Walter, O., Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2013). <i>A Novel Initialization
    Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>.
  bibtex: '@book{Walter_Schmalenstroeer_Haeb-Umbach_2013, title={A Novel Initialization
    Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)},
    author={Walter, Oliver and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold},
    year={2013} }'
  chicago: Walter, Oliver, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. <i>A Novel
    Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech
    (FGNT-2013-01)</i>, 2013.
  ieee: O. Walter, J. Schmalenstroeer, and R. Haeb-Umbach, <i>A Novel Initialization
    Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>.
    2013.
  mla: Walter, Oliver, et al. <i>A Novel Initialization Method for Unsupervised Learning
    of Acoustic Patterns in Speech (FGNT-2013-01)</i>. 2013.
  short: O. Walter, J. Schmalenstroeer, R. Haeb-Umbach, A Novel Initialization Method
    for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01), 2013.
date_created: 2019-07-12T05:30:55Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2013/WaScHa2013.pdf
oa: '1'
status: public
title: A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns
  in Speech (FGNT-2013-01)
type: report
user_id: '44006'
year: '2013'
...
---
_id: '11832'
abstract:
- lang: eng
  text: In this paper we propose an approach to retrieve the absolute geometry of
    an acoustic sensor network, consisting of spatially distributed microphone arrays,
    from reverberant speech input. The calibration relies on direction of arrival
    measurements of the individual arrays. The proposed calibration algorithm is derived
    from a maximum-likelihood approach employing circular statistics. Since a sensor
    node consists of a microphone array with known intra-array geometry, we are able
    to obtain an absolute geometry estimate, including angles and distances. Simulation
    results demonstrate the effectiveness of the approach.
author:
- first_name: Florian
  full_name: Jacob, Florian
  last_name: Jacob
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Jacob F, Schmalenstroeer J, Haeb-Umbach R. DoA-Based Microphone Array Position
    Self-Calibration Using Circular Statistic. In: <i>38th International Conference
    on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>. ; 2013:116-120.
    doi:<a href="https://doi.org/10.1109/ICASSP.2013.6637620">10.1109/ICASSP.2013.6637620</a>'
  apa: Jacob, F., Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2013). DoA-Based Microphone
    Array Position Self-Calibration Using Circular Statistic. <i>38th International
    Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>, 116–120.
    <a href="https://doi.org/10.1109/ICASSP.2013.6637620">https://doi.org/10.1109/ICASSP.2013.6637620</a>
  bibtex: '@inproceedings{Jacob_Schmalenstroeer_Haeb-Umbach_2013, title={DoA-Based
    Microphone Array Position Self-Calibration Using Circular Statistic}, DOI={<a
    href="https://doi.org/10.1109/ICASSP.2013.6637620">10.1109/ICASSP.2013.6637620</a>},
    booktitle={38th International Conference on Acoustics, Speech, and Signal Processing
    (ICASSP 2013)}, author={Jacob, Florian and Schmalenstroeer, Joerg and Haeb-Umbach,
    Reinhold}, year={2013}, pages={116–120} }'
  chicago: Jacob, Florian, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “DoA-Based
    Microphone Array Position Self-Calibration Using Circular Statistic.” In <i>38th
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>,
    116–20, 2013. <a href="https://doi.org/10.1109/ICASSP.2013.6637620">https://doi.org/10.1109/ICASSP.2013.6637620</a>.
  ieee: 'F. Jacob, J. Schmalenstroeer, and R. Haeb-Umbach, “DoA-Based Microphone Array
    Position Self-Calibration Using Circular Statistic,” in <i>38th International
    Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>, 2013,
    pp. 116–120, doi: <a href="https://doi.org/10.1109/ICASSP.2013.6637620">10.1109/ICASSP.2013.6637620</a>.'
  mla: Jacob, Florian, et al. “DoA-Based Microphone Array Position Self-Calibration
    Using Circular Statistic.” <i>38th International Conference on Acoustics, Speech,
    and Signal Processing (ICASSP 2013)</i>, 2013, pp. 116–20, doi:<a href="https://doi.org/10.1109/ICASSP.2013.6637620">10.1109/ICASSP.2013.6637620</a>.
  short: 'F. Jacob, J. Schmalenstroeer, R. Haeb-Umbach, in: 38th International Conference
    on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 116–120.'
date_created: 2019-07-12T05:29:07Z
date_updated: 2023-10-26T08:11:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6637620
keyword:
- Geometry calibration
- microphone arrays
- position self-calibration
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2013/JacSchHae_ICASSP2013_Rev2.pdf
oa: '1'
page: 116-120
publication: 38th International Conference on Acoustics, Speech, and Signal Processing
  (ICASSP 2013)
publication_identifier:
  issn:
  - 1520-6149
quality_controlled: '1'
related_material:
  link:
  - description: Presentation
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2013/JaScHa13_Presentation.pdf
status: public
title: DoA-Based Microphone Array Position Self-Calibration Using Circular Statistic
type: conference
user_id: '460'
year: '2013'
...
---
_id: '11891'
abstract:
- lang: eng
  text: In this paper we present a combined hardware/software approach for synchronizing
    the sampling clocks of an acoustic sensor network. A first clock frequency offset
    estimate is obtained by a time stamp exchange protocol with a low data rate and
    computational requirements. The estimate is then postprocessed by a Kalman filter
    which exploits the specific properties of the statistics of the frequency offset
    estimation error. In long term experiments the deviation between the sampling
    oscillators of two sensor nodes never exceeded half a sample with a wired and
    with a wireless link between the nodes. The achieved precision enables the estimation
    of time difference of arrival values across different hardware devices without
    sharing a common sampling hardware.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Schmalenstroeer J, Haeb-Umbach R. Sampling Rate Synchronisation in Acoustic
    Sensor Networks with a Pre-Trained Clock Skew Error Model. In: <i>21th European
    Signal Processing Conference (EUSIPCO 2013)</i>. ; 2013.'
  apa: Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2013). Sampling Rate Synchronisation
    in Acoustic Sensor Networks with a Pre-Trained Clock Skew Error Model. <i>21th
    European Signal Processing Conference (EUSIPCO 2013)</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Haeb-Umbach_2013, title={Sampling Rate Synchronisation
    in Acoustic Sensor Networks with a Pre-Trained Clock Skew Error Model}, booktitle={21th
    European Signal Processing Conference (EUSIPCO 2013)}, author={Schmalenstroeer,
    Joerg and Haeb-Umbach, Reinhold}, year={2013} }'
  chicago: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Sampling Rate Synchronisation
    in Acoustic Sensor Networks with a Pre-Trained Clock Skew Error Model.” In <i>21th
    European Signal Processing Conference (EUSIPCO 2013)</i>, 2013.
  ieee: J. Schmalenstroeer and R. Haeb-Umbach, “Sampling Rate Synchronisation in Acoustic
    Sensor Networks with a Pre-Trained Clock Skew Error Model,” 2013.
  mla: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Sampling Rate Synchronisation
    in Acoustic Sensor Networks with a Pre-Trained Clock Skew Error Model.” <i>21th
    European Signal Processing Conference (EUSIPCO 2013)</i>, 2013.
  short: 'J. Schmalenstroeer, R. Haeb-Umbach, in: 21th European Signal Processing
    Conference (EUSIPCO 2013), 2013.'
date_created: 2019-07-12T05:30:15Z
date_updated: 2023-10-26T08:11:01Z
department:
- _id: '54'
keyword:
- synchronization
- acoustic sensor network
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2013/SchHaeb2013.pdf
oa: '1'
publication: 21th European Signal Processing Conference (EUSIPCO 2013)
quality_controlled: '1'
related_material:
  link:
  - description: Presentation
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2013/SchHaeb2013_Presentation.pdf
status: public
title: Sampling Rate Synchronisation in Acoustic Sensor Networks with a Pre-Trained
  Clock Skew Error Model
type: conference
user_id: '460'
year: '2013'
...
---
_id: '11818'
abstract:
- lang: eng
  text: In this paper we present a system for indoor navigation based on received
    signal strength index information of Wireless-LAN access points and relative position
    estimates. The relative position information is gathered from inertial smartphone
    sensors using a step detection and an orientation estimate. Our map data is hosted
    on a server employing a map renderer and a SQL database. The database includes
    a complete multilevel office building, within which the user can navigate. During
    navigation, the client retrieves the position estimate from the server, together
    with the corresponding map tiles to visualize the user's position on the smartphone
    display.
author:
- first_name: Manh Kha
  full_name: Hoang, Manh Kha
  last_name: Hoang
- first_name: Sarah
  full_name: Schmitz, Sarah
  last_name: Schmitz
- first_name: Christian
  full_name: Drueke, Christian
  last_name: Drueke
- first_name: Dang Hai Tran
  full_name: Vu, Dang Hai Tran
  last_name: Vu
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Hoang MK, Schmitz S, Drueke C, Vu DHT, Schmalenstroeer J, Haeb-Umbach R. Server
    based indoor navigation using RSSI and inertial sensor information. In: <i>Positioning
    Navigation and Communication (WPNC), 2013 10th Workshop On</i>. ; 2013:1-6. doi:<a
    href="https://doi.org/10.1109/WPNC.2013.6533263">10.1109/WPNC.2013.6533263</a>'
  apa: Hoang, M. K., Schmitz, S., Drueke, C., Vu, D. H. T., Schmalenstroeer, J., &#38;
    Haeb-Umbach, R. (2013). Server based indoor navigation using RSSI and inertial
    sensor information. <i>Positioning Navigation and Communication (WPNC), 2013 10th
    Workshop On</i>, 1–6. <a href="https://doi.org/10.1109/WPNC.2013.6533263">https://doi.org/10.1109/WPNC.2013.6533263</a>
  bibtex: '@inproceedings{Hoang_Schmitz_Drueke_Vu_Schmalenstroeer_Haeb-Umbach_2013,
    title={Server based indoor navigation using RSSI and inertial sensor information},
    DOI={<a href="https://doi.org/10.1109/WPNC.2013.6533263">10.1109/WPNC.2013.6533263</a>},
    booktitle={Positioning Navigation and Communication (WPNC), 2013 10th Workshop
    on}, author={Hoang, Manh Kha and Schmitz, Sarah and Drueke, Christian and Vu,
    Dang Hai Tran and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2013},
    pages={1–6} }'
  chicago: Hoang, Manh Kha, Sarah Schmitz, Christian Drueke, Dang Hai Tran Vu, Joerg
    Schmalenstroeer, and Reinhold Haeb-Umbach. “Server Based Indoor Navigation Using
    RSSI and Inertial Sensor Information.” In <i>Positioning Navigation and Communication
    (WPNC), 2013 10th Workshop On</i>, 1–6, 2013. <a href="https://doi.org/10.1109/WPNC.2013.6533263">https://doi.org/10.1109/WPNC.2013.6533263</a>.
  ieee: 'M. K. Hoang, S. Schmitz, C. Drueke, D. H. T. Vu, J. Schmalenstroeer, and
    R. Haeb-Umbach, “Server based indoor navigation using RSSI and inertial sensor
    information,” in <i>Positioning Navigation and Communication (WPNC), 2013 10th
    Workshop on</i>, 2013, pp. 1–6, doi: <a href="https://doi.org/10.1109/WPNC.2013.6533263">10.1109/WPNC.2013.6533263</a>.'
  mla: Hoang, Manh Kha, et al. “Server Based Indoor Navigation Using RSSI and Inertial
    Sensor Information.” <i>Positioning Navigation and Communication (WPNC), 2013
    10th Workshop On</i>, 2013, pp. 1–6, doi:<a href="https://doi.org/10.1109/WPNC.2013.6533263">10.1109/WPNC.2013.6533263</a>.
  short: 'M.K. Hoang, S. Schmitz, C. Drueke, D.H.T. Vu, J. Schmalenstroeer, R. Haeb-Umbach,
    in: Positioning Navigation and Communication (WPNC), 2013 10th Workshop On, 2013,
    pp. 1–6.'
date_created: 2019-07-12T05:28:51Z
date_updated: 2023-10-26T08:09:36Z
department:
- _id: '54'
doi: 10.1109/WPNC.2013.6533263
keyword:
- SQL
- navigation
- smart phones
- wireless LAN
- RSSI
- SQL database
- complete multilevel office building
- inertial sensor information
- inertial smartphone sensors
- map renderer
- received signal strength index information
- relative position estimates
- server based indoor navigation
- step detection
- wireless-LAN access points
- Smartphone
- fingerprint
- indoor navigation
- map tile
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrScHa2013.pdf
oa: '1'
page: 1-6
publication: Positioning Navigation and Communication (WPNC), 2013 10th Workshop on
quality_controlled: '1'
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrScHa2013_Poster.pdf
status: public
title: Server based indoor navigation using RSSI and inertial sensor information
type: conference
user_id: '460'
year: '2013'
...
---
_id: '11817'
abstract:
- lang: eng
  text: In this paper we present a modified hidden Markov model (HMM) for the fusion
    of received signal strength index (RSSI) information of WiFi access points and
    relative position information which is obtained from the inertial sensors of a
    smartphone for indoor positioning. Since the states of the HMM represent the potential
    user locations, their number determines the quantization error introduced by discretizing
    the allowable user positions through the use of the HMM. To reduce this quantization
    error we introduce â??pseudoâ?? states, whose emission probability, which models
    the RSSI measurements at this location, is synthesized from those of the neighboring
    states of which a Gaussian emission probability has been estimated during the
    training phase. The experimental results demonstrate the effectiveness of this
    approach. By introducing on average two pseudo states per original HMM state the
    positioning error could be significantly reduced without increasing the training
    effort.
author:
- first_name: Manh Kha
  full_name: Hoang, Manh Kha
  last_name: Hoang
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Christian
  full_name: Drueke, Christian
  last_name: Drueke
- first_name: Dang Hai
  full_name: Tran Vu, Dang Hai
  last_name: Tran Vu
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Hoang MK, Schmalenstroeer J, Drueke C, Tran Vu DH, Haeb-Umbach R. A Hidden
    Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection.
    In: <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>. ; 2013.'
  apa: Hoang, M. K., Schmalenstroeer, J., Drueke, C., Tran Vu, D. H., &#38; Haeb-Umbach,
    R. (2013). A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting
    and Step Detection. <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>.
  bibtex: '@inproceedings{Hoang_Schmalenstroeer_Drueke_Tran Vu_Haeb-Umbach_2013, title={A
    Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and
    Step Detection}, booktitle={21th European Signal Processing Conference (EUSIPCO
    2013)}, author={Hoang, Manh Kha and Schmalenstroeer, Joerg and Drueke, Christian
    and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2013} }'
  chicago: Hoang, Manh Kha, Joerg Schmalenstroeer, Christian Drueke, Dang Hai Tran
    Vu, and Reinhold Haeb-Umbach. “A Hidden Markov Model for Indoor User Tracking
    Based on WiFi Fingerprinting and Step Detection.” In <i>21th European Signal Processing
    Conference (EUSIPCO 2013)</i>, 2013.
  ieee: M. K. Hoang, J. Schmalenstroeer, C. Drueke, D. H. Tran Vu, and R. Haeb-Umbach,
    “A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and
    Step Detection,” 2013.
  mla: Hoang, Manh Kha, et al. “A Hidden Markov Model for Indoor User Tracking Based
    on WiFi Fingerprinting and Step Detection.” <i>21th European Signal Processing
    Conference (EUSIPCO 2013)</i>, 2013.
  short: 'M.K. Hoang, J. Schmalenstroeer, C. Drueke, D.H. Tran Vu, R. Haeb-Umbach,
    in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013.'
date_created: 2019-07-12T05:28:50Z
date_updated: 2023-10-26T08:09:45Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrHa2013.pdf
oa: '1'
publication: 21th European Signal Processing Conference (EUSIPCO 2013)
quality_controlled: '1'
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrHa2013_Poster.pdf
status: public
title: A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting
  and Step Detection
type: conference
user_id: '460'
year: '2013'
...
---
_id: '11833'
abstract:
- lang: eng
  text: In this paper we propose an approach to retrieve the geometry of an acoustic
    sensor network consisting of spatially distributed microphone arrays from unconstrained
    speech input. The calibration relies on Direction of Arrival (DoA) measurements
    which do not require a clock synchronization among the sensor nodes. The calibration
    problem is formulated as a cost function optimization task, which minimizes the
    squared differences between measured and predicted observations and additionally
    avoids the existence of minima that correspond to mirrored versions of the actual
    sensor orientations. Further, outlier measurements caused by reverberation are
    mitigated by a Random Sample Consensus (RANSAC) approach. The experimental results
    show a mean positioning error of at most 25 cm even in highly reverberant environments.
author:
- first_name: Florian
  full_name: Jacob, Florian
  last_name: Jacob
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Jacob F, Schmalenstroeer J, Haeb-Umbach R. Microphone Array Position Self-Calibration
    from Reverberant Speech Input. In: <i>International Workshop on Acoustic Signal
    Enhancement (IWAENC 2012)</i>. ; 2012.'
  apa: Jacob, F., Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2012). Microphone Array
    Position Self-Calibration from Reverberant Speech Input. <i>International Workshop
    on Acoustic Signal Enhancement (IWAENC 2012)</i>.
  bibtex: '@inproceedings{Jacob_Schmalenstroeer_Haeb-Umbach_2012, title={Microphone
    Array Position Self-Calibration from Reverberant Speech Input}, booktitle={International
    Workshop on Acoustic Signal Enhancement (IWAENC 2012)}, author={Jacob, Florian
    and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2012} }'
  chicago: Jacob, Florian, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “Microphone
    Array Position Self-Calibration from Reverberant Speech Input.” In <i>International
    Workshop on Acoustic Signal Enhancement (IWAENC 2012)</i>, 2012.
  ieee: F. Jacob, J. Schmalenstroeer, and R. Haeb-Umbach, “Microphone Array Position
    Self-Calibration from Reverberant Speech Input,” 2012.
  mla: Jacob, Florian, et al. “Microphone Array Position Self-Calibration from Reverberant
    Speech Input.” <i>International Workshop on Acoustic Signal Enhancement (IWAENC
    2012)</i>, 2012.
  short: 'F. Jacob, J. Schmalenstroeer, R. Haeb-Umbach, in: International Workshop
    on Acoustic Signal Enhancement (IWAENC 2012), 2012.'
date_created: 2019-07-12T05:29:08Z
date_updated: 2023-10-26T08:10:52Z
department:
- _id: '54'
keyword:
- Unsupervised
- geometry calibration
- microphone arrays
- position self-calibration
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2012/JaScHa12.pdf
oa: '1'
publication: International Workshop on Acoustic Signal Enhancement (IWAENC 2012)
quality_controlled: '1'
related_material:
  link:
  - description: Video
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2012/Microphine_Array_Position_Self-Calibration_from_Reverberant_Speech_Input.mp4
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2012/JaScHa12_Poster.pdf
  - description: Demonstrator
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2012/JaScHa12_Demonstrator.pdf
status: public
title: Microphone Array Position Self-Calibration from Reverberant Speech Input
type: conference
user_id: '460'
year: '2012'
...
---
_id: '11925'
abstract:
- lang: eng
  text: In this paper we present a system for car navigation by fusing sensor data
    on an Android smartphone. The key idea is to use both the internal sensors of
    the smartphone (e.g., gyroscope) and sensor data from the car (e.g., speed information)
    to support navigation via GPS. To this end we employ a CAN-Bus-to-Bluetooth adapter
    to establish a wireless connection between the smartphone and the CAN-Bus of the
    car. On the smartphone a strapdown algorithm and an error-state Kalman filter
    are used to fuse the different sensor data streams. The experimental results show
    that the system is able to maintain higher positioning accuracy during GPS dropouts,
    thus improving the availability and reliability, compared to GPS-only solutions.
author:
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Andreas
  full_name: Engler, Andreas
  last_name: Engler
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Walter O, Schmalenstroeer J, Engler A, Haeb-Umbach R. Smartphone-Based Sensor
    Fusion for Improved Vehicular Navigation. In: <i>9th Workshop on Positioning Navigation
    and Communication (WPNC 2012)</i>. ; 2012.'
  apa: Walter, O., Schmalenstroeer, J., Engler, A., &#38; Haeb-Umbach, R. (2012).
    Smartphone-Based Sensor Fusion for Improved Vehicular Navigation. <i>9th Workshop
    on Positioning Navigation and Communication (WPNC 2012)</i>.
  bibtex: '@inproceedings{Walter_Schmalenstroeer_Engler_Haeb-Umbach_2012, title={Smartphone-Based
    Sensor Fusion for Improved Vehicular Navigation}, booktitle={9th Workshop on Positioning
    Navigation and Communication (WPNC 2012)}, author={Walter, Oliver and Schmalenstroeer,
    Joerg and Engler, Andreas and Haeb-Umbach, Reinhold}, year={2012} }'
  chicago: Walter, Oliver, Joerg Schmalenstroeer, Andreas Engler, and Reinhold Haeb-Umbach.
    “Smartphone-Based Sensor Fusion for Improved Vehicular Navigation.” In <i>9th
    Workshop on Positioning Navigation and Communication (WPNC 2012)</i>, 2012.
  ieee: O. Walter, J. Schmalenstroeer, A. Engler, and R. Haeb-Umbach, “Smartphone-Based
    Sensor Fusion for Improved Vehicular Navigation,” 2012.
  mla: Walter, Oliver, et al. “Smartphone-Based Sensor Fusion for Improved Vehicular
    Navigation.” <i>9th Workshop on Positioning Navigation and Communication (WPNC
    2012)</i>, 2012.
  short: 'O. Walter, J. Schmalenstroeer, A. Engler, R. Haeb-Umbach, in: 9th Workshop
    on Positioning Navigation and Communication (WPNC 2012), 2012.'
date_created: 2019-07-12T05:30:54Z
date_updated: 2023-10-26T08:13:27Z
department:
- _id: '54'
keyword:
- Smartphone
- navigation
- sensor fusion
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2012/WaScEnHa12.pdf
oa: '1'
publication: 9th Workshop on Positioning Navigation and Communication (WPNC 2012)
quality_controlled: '1'
status: public
title: Smartphone-Based Sensor Fusion for Improved Vehicular Navigation
type: conference
user_id: '460'
year: '2012'
...
---
_id: '11889'
abstract:
- lang: eng
  text: In this paper we propose to jointly consider Segmental Dynamic Time Warping
    and distance clustering for the unsupervised learning of acoustic events. As a
    result, the computational complexity increases only linearly with the dababase
    size compared to a quadratic increase in a sequential setup, where all pairwise
    SDTW distances between segments are computed prior to clustering. Further, we
    discuss options for seed value selection for clustering and show that drawing
    seeds with a probability proportional to the distance from the already drawn seeds,
    known as K-means++ clustering, results in a significantly higher probability of
    finding representatives of each of the underlying classes, compared to the commonly
    used draws from a uniform distribution. Experiments are performed on an acoustic
    event classification and an isolated digit recognition task, where on the latter
    the final word accuracy approaches that of supervised training.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Markus
  full_name: Bartek, Markus
  last_name: Bartek
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Schmalenstroeer J, Bartek M, Haeb-Umbach R. Unsupervised learning of acoustic
    events using dynamic time warping and hierarchical K-means++ clustering. In: <i>Interspeech
    2011</i>. ; 2011.'
  apa: Schmalenstroeer, J., Bartek, M., &#38; Haeb-Umbach, R. (2011). Unsupervised
    learning of acoustic events using dynamic time warping and hierarchical K-means++
    clustering. <i>Interspeech 2011</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Bartek_Haeb-Umbach_2011, title={Unsupervised
    learning of acoustic events using dynamic time warping and hierarchical K-means++
    clustering}, booktitle={Interspeech 2011}, author={Schmalenstroeer, Joerg and
    Bartek, Markus and Haeb-Umbach, Reinhold}, year={2011} }'
  chicago: Schmalenstroeer, Joerg, Markus Bartek, and Reinhold Haeb-Umbach. “Unsupervised
    Learning of Acoustic Events Using Dynamic Time Warping and Hierarchical K-Means++
    Clustering.” In <i>Interspeech 2011</i>, 2011.
  ieee: J. Schmalenstroeer, M. Bartek, and R. Haeb-Umbach, “Unsupervised learning
    of acoustic events using dynamic time warping and hierarchical K-means++ clustering,”
    2011.
  mla: Schmalenstroeer, Joerg, et al. “Unsupervised Learning of Acoustic Events Using
    Dynamic Time Warping and Hierarchical K-Means++ Clustering.” <i>Interspeech 2011</i>,
    2011.
  short: 'J. Schmalenstroeer, M. Bartek, R. Haeb-Umbach, in: Interspeech 2011, 2011.'
date_created: 2019-07-12T05:30:13Z
date_updated: 2023-10-26T08:10:44Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2011/ScBaHa11-2.pdf
oa: '1'
publication: Interspeech 2011
quality_controlled: '1'
status: public
title: Unsupervised learning of acoustic events using dynamic time warping and hierarchical
  K-means++ clustering
type: conference
user_id: '460'
year: '2011'
...
---
_id: '11896'
abstract:
- lang: eng
  text: In this paper we propose a procedure for estimating the geometric configuration
    of an arbitrary acoustic sensor placement. It determines the position and the
    orientation of microphone arrays in 2D while locating a source by direction-of-arrival
    (DoA) estimation. Neither artificial calibration signals nor unnatural user activity
    are required. The problem of scale indeterminacy inherent to DoA-only observations
    is solved by adding time difference of arrival (TDOA) measurements. The geometry
    calibration method is numerically stable and delivers precise results in moderately
    reverberated rooms. Simulation results are confirmed by laboratory experiments.
author:
- first_name: Joerg
  full_name: Schmalenstroeer, Joerg
  id: '460'
  last_name: Schmalenstroeer
- first_name: Florian
  full_name: Jacob, Florian
  last_name: Jacob
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
- first_name: Marius
  full_name: Hennecke, Marius
  last_name: Hennecke
- first_name: Gernot A.
  full_name: Fink, Gernot A.
  last_name: Fink
citation:
  ama: 'Schmalenstroeer J, Jacob F, Haeb-Umbach R, Hennecke M, Fink GA. Unsupervised
    Geometry Calibration of Acoustic Sensor Networks Using Source Correspondences.
    In: <i>Interspeech 2011</i>. ; 2011.'
  apa: Schmalenstroeer, J., Jacob, F., Haeb-Umbach, R., Hennecke, M., &#38; Fink,
    G. A. (2011). Unsupervised Geometry Calibration of Acoustic Sensor Networks Using
    Source Correspondences. <i>Interspeech 2011</i>.
  bibtex: '@inproceedings{Schmalenstroeer_Jacob_Haeb-Umbach_Hennecke_Fink_2011, title={Unsupervised
    Geometry Calibration of Acoustic Sensor Networks Using Source Correspondences},
    booktitle={Interspeech 2011}, author={Schmalenstroeer, Joerg and Jacob, Florian
    and Haeb-Umbach, Reinhold and Hennecke, Marius and Fink, Gernot A.}, year={2011}
    }'
  chicago: Schmalenstroeer, Joerg, Florian Jacob, Reinhold Haeb-Umbach, Marius Hennecke,
    and Gernot A. Fink. “Unsupervised Geometry Calibration of Acoustic Sensor Networks
    Using Source Correspondences.” In <i>Interspeech 2011</i>, 2011.
  ieee: J. Schmalenstroeer, F. Jacob, R. Haeb-Umbach, M. Hennecke, and G. A. Fink,
    “Unsupervised Geometry Calibration of Acoustic Sensor Networks Using Source Correspondences,”
    2011.
  mla: Schmalenstroeer, Joerg, et al. “Unsupervised Geometry Calibration of Acoustic
    Sensor Networks Using Source Correspondences.” <i>Interspeech 2011</i>, 2011.
  short: 'J. Schmalenstroeer, F. Jacob, R. Haeb-Umbach, M. Hennecke, G.A. Fink, in:
    Interspeech 2011, 2011.'
date_created: 2019-07-12T05:30:21Z
date_updated: 2023-10-26T08:10:28Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2011/ScJaHaHeFi11.pdf
oa: '1'
publication: Interspeech 2011
quality_controlled: '1'
status: public
title: Unsupervised Geometry Calibration of Acoustic Sensor Networks Using Source
  Correspondences
type: conference
user_id: '460'
year: '2011'
...