---
_id: '11771'
abstract:
- lang: eng
  text: This paper is concerned with speech presence probability estimation employing
    an explicit model of the temporal and spectral correlations of speech. An undirected
    graphical model is introduced, based on a Factor Graph formulation. It is shown
    that this undirected model cures some of the theoretical issues of an earlier
    directed graphical model. Furthermore, we formulate a message passing inference
    scheme based on an approximate graph factorization, identify this inference scheme
    as a particular message passing schedule based on the turbo principle and suggest
    further alternative schedules. The experiments show an improved performance over
    speech presence probability estimation based on an IID assumption, and a slightly
    better performance of the turbo schedule over the alternatives.
author:
- first_name: Thomas
  full_name: Glarner, Thomas
  id: '14169'
  last_name: Glarner
- first_name: Mohammad
  full_name: Mahdi Momenzadeh, Mohammad
  last_name: Mahdi Momenzadeh
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Glarner T, Mahdi Momenzadeh M, Drude L, Haeb-Umbach R. Factor Graph Decoding
    for Speech Presence Probability Estimation. In: <i>12. ITG Fachtagung Sprachkommunikation
    (ITG 2016)</i>. ; 2016.'
  apa: Glarner, T., Mahdi Momenzadeh, M., Drude, L., &#38; Haeb-Umbach, R. (2016).
    Factor Graph Decoding for Speech Presence Probability Estimation. In <i>12. ITG
    Fachtagung Sprachkommunikation (ITG 2016)</i>.
  bibtex: '@inproceedings{Glarner_Mahdi Momenzadeh_Drude_Haeb-Umbach_2016, title={Factor
    Graph Decoding for Speech Presence Probability Estimation}, booktitle={12. ITG
    Fachtagung Sprachkommunikation (ITG 2016)}, author={Glarner, Thomas and Mahdi
    Momenzadeh, Mohammad and Drude, Lukas and Haeb-Umbach, Reinhold}, year={2016}
    }'
  chicago: Glarner, Thomas, Mohammad Mahdi Momenzadeh, Lukas Drude, and Reinhold Haeb-Umbach.
    “Factor Graph Decoding for Speech Presence Probability Estimation.” In <i>12.
    ITG Fachtagung Sprachkommunikation (ITG 2016)</i>, 2016.
  ieee: T. Glarner, M. Mahdi Momenzadeh, L. Drude, and R. Haeb-Umbach, “Factor Graph
    Decoding for Speech Presence Probability Estimation,” in <i>12. ITG Fachtagung
    Sprachkommunikation (ITG 2016)</i>, 2016.
  mla: Glarner, Thomas, et al. “Factor Graph Decoding for Speech Presence Probability
    Estimation.” <i>12. ITG Fachtagung Sprachkommunikation (ITG 2016)</i>, 2016.
  short: 'T. Glarner, M. Mahdi Momenzadeh, L. Drude, R. Haeb-Umbach, in: 12. ITG Fachtagung
    Sprachkommunikation (ITG 2016), 2016.'
date_created: 2019-07-12T05:27:56Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2016/itgspeech2016_08_Glarner.pdf
oa: '1'
publication: 12. ITG Fachtagung Sprachkommunikation (ITG 2016)
related_material:
  link:
  - description: Slides
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2016/itgspeech2016_08_Glarner_slides.pdf
status: public
title: Factor Graph Decoding for Speech Presence Probability Estimation
type: conference
user_id: '44006'
year: '2016'
...
---
_id: '11812'
author:
- 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: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Heymann J, Drude L, Haeb-Umbach R. Neural Network Based Spectral Mask Estimation
    for Acoustic Beamforming. In: <i>Proc. IEEE Intl. Conf. on Acoustics, Speech and
    Signal Processing (ICASSP)</i>. ; 2016.'
  apa: Heymann, J., Drude, L., &#38; Haeb-Umbach, R. (2016). Neural Network Based
    Spectral Mask Estimation for Acoustic Beamforming. In <i>Proc. IEEE Intl. Conf.
    on Acoustics, Speech and Signal Processing (ICASSP)</i>.
  bibtex: '@inproceedings{Heymann_Drude_Haeb-Umbach_2016, title={Neural Network Based
    Spectral Mask Estimation for Acoustic Beamforming}, booktitle={Proc. IEEE Intl.
    Conf. on Acoustics, Speech and Signal Processing (ICASSP)}, author={Heymann, Jahn
    and Drude, Lukas and Haeb-Umbach, Reinhold}, year={2016} }'
  chicago: Heymann, Jahn, Lukas Drude, and Reinhold Haeb-Umbach. “Neural Network Based
    Spectral Mask Estimation for Acoustic Beamforming.” In <i>Proc. IEEE Intl. Conf.
    on Acoustics, Speech and Signal Processing (ICASSP)</i>, 2016.
  ieee: J. Heymann, L. Drude, and R. Haeb-Umbach, “Neural Network Based Spectral Mask
    Estimation for Acoustic Beamforming,” in <i>Proc. IEEE Intl. Conf. on Acoustics,
    Speech and Signal Processing (ICASSP)</i>, 2016.
  mla: Heymann, Jahn, et al. “Neural Network Based Spectral Mask Estimation for Acoustic
    Beamforming.” <i>Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing
    (ICASSP)</i>, 2016.
  short: 'J. Heymann, L. Drude, R. Haeb-Umbach, in: Proc. IEEE Intl. Conf. on Acoustics,
    Speech and Signal Processing (ICASSP), 2016.'
date_created: 2019-07-12T05:28:44Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2016/icassp_2016_heymann_paper.pdf
oa: '1'
publication: Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
related_material:
  link:
  - description: Slides
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2016/icassp_2016_heymann_slides.pdf
status: public
title: Neural Network Based Spectral Mask Estimation for Acoustic Beamforming
type: conference
user_id: '44006'
year: '2016'
...
---
_id: '11829'
abstract:
- lang: eng
  text: 'This contribution investigates Direction of Arrival (DoA) estimation using
    linearly arranged microphone arrays. We are going to develop a model for the DoA
    estimation error in a reverberant scenario and show the existence of a bias, that
    is a consequence of the linear arrangement and limited field of view (FoV) bias:
    First, the limited FoV leading to a clipping of the measurements, and, second,
    the angular distribution of the signal energy of the reflections being non-uniform.
    Since both issues are a consequence of the linear arrangement of the sensors,
    the bias arises largely independent of the kind of DoA estimator. The experimental
    evaluation demonstrates the existence of the bias for a selected number of DoA
    estimation methods and proves that the prediction from the developed theoretical
    model matches the simulation results.'
author:
- first_name: Florian
  full_name: Jacob, Florian
  last_name: Jacob
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Jacob F, Haeb-Umbach R. On the Bias of Direction of Arrival Estimation Using
    Linear Microphone Arrays. In: <i>12. ITG Fachtagung Sprachkommunikation (ITG 2016)</i>.
    ; 2016.'
  apa: Jacob, F., &#38; Haeb-Umbach, R. (2016). On the Bias of Direction of Arrival
    Estimation Using Linear Microphone Arrays. In <i>12. ITG Fachtagung Sprachkommunikation
    (ITG 2016)</i>.
  bibtex: '@inproceedings{Jacob_Haeb-Umbach_2016, title={On the Bias of Direction
    of Arrival Estimation Using Linear Microphone Arrays}, booktitle={12. ITG Fachtagung
    Sprachkommunikation (ITG 2016)}, author={Jacob, Florian and Haeb-Umbach, Reinhold},
    year={2016} }'
  chicago: Jacob, Florian, and Reinhold Haeb-Umbach. “On the Bias of Direction of
    Arrival Estimation Using Linear Microphone Arrays.” In <i>12. ITG Fachtagung Sprachkommunikation
    (ITG 2016)</i>, 2016.
  ieee: F. Jacob and R. Haeb-Umbach, “On the Bias of Direction of Arrival Estimation
    Using Linear Microphone Arrays,” in <i>12. ITG Fachtagung Sprachkommunikation
    (ITG 2016)</i>, 2016.
  mla: Jacob, Florian, and Reinhold Haeb-Umbach. “On the Bias of Direction of Arrival
    Estimation Using Linear Microphone Arrays.” <i>12. ITG Fachtagung Sprachkommunikation
    (ITG 2016)</i>, 2016.
  short: 'F. Jacob, R. Haeb-Umbach, in: 12. ITG Fachtagung Sprachkommunikation (ITG
    2016), 2016.'
date_created: 2019-07-12T05:29:03Z
date_updated: 2022-01-06T06:51:10Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2016/JacobHaeb_ITG2016.pdf
oa: '1'
publication: 12. ITG Fachtagung Sprachkommunikation (ITG 2016)
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2016/JacobHaeb_ITG2016_poster.pdf
status: public
title: On the Bias of Direction of Arrival Estimation Using Linear Microphone Arrays
type: conference
user_id: '44006'
year: '2016'
...
---
_id: '11834'
abstract:
- lang: eng
  text: We present a system for the 4th CHiME challenge which significantly increases
    the performance for all three tracks with respect to the provided baseline system.
    The front-end uses a bi-directional Long Short-Term Memory (BLSTM)-based neural
    network to estimate signal statistics. These then steer a Generalized Eigenvalue
    beamformer. The back-end consists of a 22 layer deep Wide Residual Network and
    two extra BLSTM layers. Working on a whole utterance instead of frames allows
    us to refine Batch-Normalization. We also train our own BLSTM-based language model.
    Adding a discriminative speaker adaptation leads to further gains. The final system
    achieves a word error rate on the six channel real test data of 3.48%. For the
    two channel track we achieve 5.96% and for the one channel track 9.34%. This is
    the best reported performance on the challenge achieved by a single system, i.e.,
    a configuration, which does not combine multiple systems. At the same time, our
    system is independent of the microphone configuration. We can thus use the same
    components for all three tracks.
author:
- 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: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Heymann J, Drude L, Haeb-Umbach R. Wide Residual BLSTM Network with Discriminative
    Speaker Adaptation for Robust Speech Recognition. In: <i>Computer Speech and Language</i>.
    ; 2016.'
  apa: Heymann, J., Drude, L., &#38; Haeb-Umbach, R. (2016). Wide Residual BLSTM Network
    with Discriminative Speaker Adaptation for Robust Speech Recognition. In <i>Computer
    Speech and Language</i>.
  bibtex: '@inproceedings{Heymann_Drude_Haeb-Umbach_2016, title={Wide Residual BLSTM
    Network with Discriminative Speaker Adaptation for Robust Speech Recognition},
    booktitle={Computer Speech and Language}, author={Heymann, Jahn and Drude, Lukas
    and Haeb-Umbach, Reinhold}, year={2016} }'
  chicago: Heymann, Jahn, Lukas Drude, and Reinhold Haeb-Umbach. “Wide Residual BLSTM
    Network with Discriminative Speaker Adaptation for Robust Speech Recognition.”
    In <i>Computer Speech and Language</i>, 2016.
  ieee: J. Heymann, L. Drude, and R. Haeb-Umbach, “Wide Residual BLSTM Network with
    Discriminative Speaker Adaptation for Robust Speech Recognition,” in <i>Computer
    Speech and Language</i>, 2016.
  mla: Heymann, Jahn, et al. “Wide Residual BLSTM Network with Discriminative Speaker
    Adaptation for Robust Speech Recognition.” <i>Computer Speech and Language</i>,
    2016.
  short: 'J. Heymann, L. Drude, R. Haeb-Umbach, in: Computer Speech and Language,
    2016.'
date_created: 2019-07-12T05:29:09Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2016/chime4_upbonly_paper.pdf
oa: '1'
publication: Computer Speech and Language
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2016/chime4_upbonly_poster.pdf
status: public
title: Wide Residual BLSTM Network with Discriminative Speaker Adaptation for Robust
  Speech Recognition
type: conference
user_id: '44006'
year: '2016'
...
---
_id: '11840'
author:
- first_name: Keisuke
  full_name: Kinoshita, Keisuke
  last_name: Kinoshita
- first_name: Marc
  full_name: Delcroix, Marc
  last_name: Delcroix
- first_name: Sharon
  full_name: Gannot, Sharon
  last_name: Gannot
- first_name: Emanuel A. P.
  full_name: Habets, Emanuel A. P.
  last_name: Habets
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
- first_name: Walter
  full_name: Kellermann, Walter
  last_name: Kellermann
- first_name: Volker
  full_name: Leutnant, Volker
  last_name: Leutnant
- first_name: Roland
  full_name: Maas, Roland
  last_name: Maas
- first_name: Tomohiro
  full_name: Nakatani, Tomohiro
  last_name: Nakatani
- first_name: Bhiksha
  full_name: Raj, Bhiksha
  last_name: Raj
- first_name: Armin
  full_name: Sehr, Armin
  last_name: Sehr
- first_name: Takuya
  full_name: Yoshioka, Takuya
  last_name: Yoshioka
citation:
  ama: 'Kinoshita K, Delcroix M, Gannot S, et al. A summary of the REVERB challenge:
    state-of-the-art and remaining challenges in reverberant speech processing research.
    <i>EURASIP Journal on Advances in Signal Processing</i>. 2016.'
  apa: 'Kinoshita, K., Delcroix, M., Gannot, S., Habets, E. A. P., Haeb-Umbach, R.,
    Kellermann, W., … Yoshioka, T. (2016). A summary of the REVERB challenge: state-of-the-art
    and remaining challenges in reverberant speech processing research. <i>EURASIP
    Journal on Advances in Signal Processing</i>.'
  bibtex: '@article{Kinoshita_Delcroix_Gannot_Habets_Haeb-Umbach_Kellermann_Leutnant_Maas_Nakatani_Raj_et
    al._2016, title={A summary of the REVERB challenge: state-of-the-art and remaining
    challenges in reverberant speech processing research}, journal={EURASIP Journal
    on Advances in Signal Processing}, author={Kinoshita, Keisuke and Delcroix, Marc
    and Gannot, Sharon and Habets, Emanuel A. P. and Haeb-Umbach, Reinhold and Kellermann,
    Walter and Leutnant, Volker and Maas, Roland and Nakatani, Tomohiro and Raj, Bhiksha
    and et al.}, year={2016} }'
  chicago: 'Kinoshita, Keisuke, Marc Delcroix, Sharon Gannot, Emanuel A. P. Habets,
    Reinhold Haeb-Umbach, Walter Kellermann, Volker Leutnant, et al. “A Summary of
    the REVERB Challenge: State-of-the-Art and Remaining Challenges in Reverberant
    Speech Processing Research.” <i>EURASIP Journal on Advances in Signal Processing</i>,
    2016.'
  ieee: 'K. Kinoshita <i>et al.</i>, “A summary of the REVERB challenge: state-of-the-art
    and remaining challenges in reverberant speech processing research,” <i>EURASIP
    Journal on Advances in Signal Processing</i>, 2016.'
  mla: 'Kinoshita, Keisuke, et al. “A Summary of the REVERB Challenge: State-of-the-Art
    and Remaining Challenges in Reverberant Speech Processing Research.” <i>EURASIP
    Journal on Advances in Signal Processing</i>, 2016.'
  short: K. Kinoshita, M. Delcroix, S. Gannot, E.A.P. Habets, R. Haeb-Umbach, W. Kellermann,
    V. Leutnant, R. Maas, T. Nakatani, B. Raj, A. Sehr, T. Yoshioka, EURASIP Journal
    on Advances in Signal Processing (2016).
date_created: 2019-07-12T05:29:16Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2016/REVERB_summary.pdf
oa: '1'
publication: EURASIP Journal on Advances in Signal Processing
status: public
title: 'A summary of the REVERB challenge: state-of-the-art and remaining challenges
  in reverberant speech processing research'
type: journal_article
user_id: '44006'
year: '2016'
...
---
_id: '11886'
abstract:
- lang: eng
  text: Today, we are often surrounded by devices with one or more microphones, such
    as smartphones, laptops, and wireless microphones. If they are part of an acoustic
    sensor network, their distribution in the environment can be beneficially exploited
    for various speech processing tasks. However, applications like speaker localization,
    speaker tracking, and speech enhancement by beamforming avail themselves of the
    geometrical configuration of the sensors. Therefore, acoustic microphone geometry
    calibration has recently become a very active field of research. This article
    provides an application-oriented, comprehensive survey of existing methods for
    microphone position self-calibration, which will be categorized by the measurements
    they use and the scenarios they can calibrate. Selected methods will be evaluated
    comparatively with real-world recordings.
author:
- first_name: Axel
  full_name: Plinge, Axel
  last_name: Plinge
- 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: Gernot A.
  full_name: Fink, Gernot A.
  last_name: Fink
citation:
  ama: 'Plinge A, Jacob F, Haeb-Umbach R, Fink GA. Acoustic Microphone Geometry Calibration:
    An overview and experimental evaluation of state-of-the-art algorithms. <i>IEEE
    Signal Processing Magazine</i>. 2016;33(4):14-29. doi:<a href="https://doi.org/10.1109/MSP.2016.2555198">10.1109/MSP.2016.2555198</a>'
  apa: 'Plinge, A., Jacob, F., Haeb-Umbach, R., &#38; Fink, G. A. (2016). Acoustic
    Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art
    algorithms. <i>IEEE Signal Processing Magazine</i>, <i>33</i>(4), 14–29. <a href="https://doi.org/10.1109/MSP.2016.2555198">https://doi.org/10.1109/MSP.2016.2555198</a>'
  bibtex: '@article{Plinge_Jacob_Haeb-Umbach_Fink_2016, title={Acoustic Microphone
    Geometry Calibration: An overview and experimental evaluation of state-of-the-art
    algorithms}, volume={33}, DOI={<a href="https://doi.org/10.1109/MSP.2016.2555198">10.1109/MSP.2016.2555198</a>},
    number={4}, journal={IEEE Signal Processing Magazine}, author={Plinge, Axel and
    Jacob, Florian and Haeb-Umbach, Reinhold and Fink, Gernot A.}, year={2016}, pages={14–29}
    }'
  chicago: 'Plinge, Axel, Florian Jacob, Reinhold Haeb-Umbach, and Gernot A. Fink.
    “Acoustic Microphone Geometry Calibration: An Overview and Experimental Evaluation
    of State-of-the-Art Algorithms.” <i>IEEE Signal Processing Magazine</i> 33, no.
    4 (2016): 14–29. <a href="https://doi.org/10.1109/MSP.2016.2555198">https://doi.org/10.1109/MSP.2016.2555198</a>.'
  ieee: 'A. Plinge, F. Jacob, R. Haeb-Umbach, and G. A. Fink, “Acoustic Microphone
    Geometry Calibration: An overview and experimental evaluation of state-of-the-art
    algorithms,” <i>IEEE Signal Processing Magazine</i>, vol. 33, no. 4, pp. 14–29,
    2016.'
  mla: 'Plinge, Axel, et al. “Acoustic Microphone Geometry Calibration: An Overview
    and Experimental Evaluation of State-of-the-Art Algorithms.” <i>IEEE Signal Processing
    Magazine</i>, vol. 33, no. 4, 2016, pp. 14–29, doi:<a href="https://doi.org/10.1109/MSP.2016.2555198">10.1109/MSP.2016.2555198</a>.'
  short: A. Plinge, F. Jacob, R. Haeb-Umbach, G.A. Fink, IEEE Signal Processing Magazine
    33 (2016) 14–29.
date_created: 2019-07-12T05:30:09Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/MSP.2016.2555198
intvolume: '        33'
issue: '4'
keyword:
- Acoustic sensors
- Microphones
- Portable computers
- Smart phones
- Wireless communication
- Wireless sensor networks
language:
- iso: eng
page: 14-29
publication: IEEE Signal Processing Magazine
publication_identifier:
  issn:
  - 1053-5888
status: public
title: 'Acoustic Microphone Geometry Calibration: An overview and experimental evaluation
  of state-of-the-art algorithms'
type: journal_article
user_id: '44006'
volume: 33
year: '2016'
...
---
_id: '11908'
abstract:
- lang: eng
  text: 'This paper describes automatic speech recognition (ASR) systems developed
    jointly by RWTH, UPB and FORTH for the 1ch, 2ch and 6ch track of the 4th CHiME
    Challenge. In the 2ch and 6ch tracks the final system output is obtained by a
    Confusion Network Combination (CNC) of multiple systems. The Acoustic Model (AM)
    is a deep neural network based on Bidirectional Long Short-Term Memory (BLSTM)
    units. The systems differ by front ends and training sets used for the acoustic
    training. The model for the 1ch track is trained without any preprocessing. For
    each front end we trained and evaluated individual acoustic models. We compare
    the ASR performance of different beamforming approaches: a conventional superdirective
    beamformer [1] and an MVDR beamformer as in [2], where the steering vector is
    estimated based on [3]. Furthermore we evaluated a BLSTM supported Generalized
    Eigenvalue beamformer using NN-GEV [4]. The back end is implemented using RWTH?s
    open-source toolkits RASR [5], RETURNN [6] and rwthlm [7]. We rescore lattices
    with a Long Short-Term Memory (LSTM) based language model. The overall best results
    are obtained by a system combination that includes the lattices from the system
    of UPB?s submission [8]. Our final submission scored second in each of the three
    tracks of the 4th CHiME Challenge.'
author:
- first_name: Tobias
  full_name: Menne, Tobias
  last_name: Menne
- first_name: Jahn
  full_name: Heymann, Jahn
  id: '9168'
  last_name: Heymann
- first_name: Anastasios
  full_name: Alexandridis, Anastasios
  last_name: Alexandridis
- first_name: Kazuki
  full_name: Irie, Kazuki
  last_name: Irie
- first_name: Albert
  full_name: Zeyer, Albert
  last_name: Zeyer
- first_name: Markus
  full_name: Kitza, Markus
  last_name: Kitza
- first_name: Pavel
  full_name: Golik, Pavel
  last_name: Golik
- first_name: Ilia
  full_name: Kulikov, Ilia
  last_name: Kulikov
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Ralf
  full_name: Schlüter, Ralf
  last_name: Schlüter
- first_name: Hermann
  full_name: Ney, Hermann
  last_name: Ney
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
- first_name: Athanasios
  full_name: Mouchtaris, Athanasios
  last_name: Mouchtaris
citation:
  ama: 'Menne T, Heymann J, Alexandridis A, et al. The RWTH/UPB/FORTH System Combination
    for the 4th CHiME Challenge Evaluation. In: <i>Computer Speech and Language</i>.
    ; 2016.'
  apa: Menne, T., Heymann, J., Alexandridis, A., Irie, K., Zeyer, A., Kitza, M., …
    Mouchtaris, A. (2016). The RWTH/UPB/FORTH System Combination for the 4th CHiME
    Challenge Evaluation. In <i>Computer Speech and Language</i>.
  bibtex: '@inproceedings{Menne_Heymann_Alexandridis_Irie_Zeyer_Kitza_Golik_Kulikov_Drude_Schlüter_et
    al._2016, title={The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge
    Evaluation}, booktitle={Computer Speech and Language}, author={Menne, Tobias and
    Heymann, Jahn and Alexandridis, Anastasios and Irie, Kazuki and Zeyer, Albert
    and Kitza, Markus and Golik, Pavel and Kulikov, Ilia and Drude, Lukas and Schlüter,
    Ralf and et al.}, year={2016} }'
  chicago: Menne, Tobias, Jahn Heymann, Anastasios Alexandridis, Kazuki Irie, Albert
    Zeyer, Markus Kitza, Pavel Golik, et al. “The RWTH/UPB/FORTH System Combination
    for the 4th CHiME Challenge Evaluation.” In <i>Computer Speech and Language</i>,
    2016.
  ieee: T. Menne <i>et al.</i>, “The RWTH/UPB/FORTH System Combination for the 4th
    CHiME Challenge Evaluation,” in <i>Computer Speech and Language</i>, 2016.
  mla: Menne, Tobias, et al. “The RWTH/UPB/FORTH System Combination for the 4th CHiME
    Challenge Evaluation.” <i>Computer Speech and Language</i>, 2016.
  short: 'T. Menne, J. Heymann, A. Alexandridis, K. Irie, A. Zeyer, M. Kitza, P. Golik,
    I. Kulikov, L. Drude, R. Schlüter, H. Ney, R. Haeb-Umbach, A. Mouchtaris, in:
    Computer Speech and Language, 2016.'
date_created: 2019-07-12T05:30:35Z
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/2016/chime4_rwthupbforth_paper.pdf
oa: '1'
publication: Computer Speech and Language
status: public
title: The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge Evaluation
type: conference
user_id: '44006'
year: '2016'
...
---
_id: '11920'
abstract:
- lang: eng
  text: In this paper we demonstrate an algorithm to learn words from speech using
    non-parametric Bayesian hierarchical models in an unsupervised setting. We exploit
    the assumption of a hierarchical structure of speech, namely the formation of
    spoken words as a sequence of phonemes. We employ the Nested Hierarchical Pitman-Yor
    Language Model, which allows an a priori unknown and possibly unlimited number
    of words. We assume the n-gram probabilities of words, the m-gram probabilities
    of phoneme sequences in words and the phoneme sequences of the words themselves
    as latent variables to be learned. We evaluate the algorithm on a cross language
    task using an existing speech recognizer trained on English speech to decode speech
    in the Xitsonga language supplied for the 2015 ZeroSpeech challenge. We apply
    the learning algorithm on the resulting phoneme graphs and achieve the highest
    token precision and F score compared to present systems.
author:
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Walter O, Haeb-Umbach R. Unsupervised Word Discovery from Speech using Bayesian
    Hierarchical Models. In: <i>38th German Conference on Pattern Recognition (GCPR
    2016)</i>. ; 2016.'
  apa: Walter, O., &#38; Haeb-Umbach, R. (2016). Unsupervised Word Discovery from
    Speech using Bayesian Hierarchical Models. In <i>38th German Conference on Pattern
    Recognition (GCPR 2016)</i>.
  bibtex: '@inproceedings{Walter_Haeb-Umbach_2016, title={Unsupervised Word Discovery
    from Speech using Bayesian Hierarchical Models}, booktitle={38th German Conference
    on Pattern Recognition (GCPR 2016)}, author={Walter, Oliver and Haeb-Umbach, Reinhold},
    year={2016} }'
  chicago: Walter, Oliver, and Reinhold Haeb-Umbach. “Unsupervised Word Discovery
    from Speech Using Bayesian Hierarchical Models.” In <i>38th German Conference
    on Pattern Recognition (GCPR 2016)</i>, 2016.
  ieee: O. Walter and R. Haeb-Umbach, “Unsupervised Word Discovery from Speech using
    Bayesian Hierarchical Models,” in <i>38th German Conference on Pattern Recognition
    (GCPR 2016)</i>, 2016.
  mla: Walter, Oliver, and Reinhold Haeb-Umbach. “Unsupervised Word Discovery from
    Speech Using Bayesian Hierarchical Models.” <i>38th German Conference on Pattern
    Recognition (GCPR 2016)</i>, 2016.
  short: 'O. Walter, R. Haeb-Umbach, in: 38th German Conference on Pattern Recognition
    (GCPR 2016), 2016.'
date_created: 2019-07-12T05:30:49Z
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/2016/WaHa16.pdf
oa: '1'
publication: 38th German Conference on Pattern Recognition (GCPR 2016)
related_material:
  link:
  - description: Presentation
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2016/WaHa16_Talk.pdf
status: public
title: Unsupervised Word Discovery from Speech using Bayesian Hierarchical Models
type: conference
user_id: '44006'
year: '2016'
...
---
_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: '11739'
abstract:
- lang: eng
  text: Noise tracking is an important component of speech enhancement algorithms.
    Of the many noise trackers proposed, Minimum Statistics (MS) is a particularly
    popular one due to its simple parameterization and at the same time excellent
    performance. In this paper we propose to further reduce the number of MS parameters
    by giving an alternative derivation of an optimal smoothing constant. At the same
    time the noise tracking performance is improved as is demonstrated by experiments
    employing speech degraded by various noise types and at different SNR values.
author:
- first_name: Aleksej
  full_name: Chinaev, Aleksej
  last_name: Chinaev
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Chinaev A, Haeb-Umbach R. On Optimal Smoothing in Minimum Statistics Based
    Noise Tracking. In: <i>Interspeech 2015</i>. ; 2015:1785-1789.'
  apa: Chinaev, A., &#38; Haeb-Umbach, R. (2015). On Optimal Smoothing in Minimum
    Statistics Based Noise Tracking. In <i>Interspeech 2015</i> (pp. 1785–1789).
  bibtex: '@inproceedings{Chinaev_Haeb-Umbach_2015, title={On Optimal Smoothing in
    Minimum Statistics Based Noise Tracking}, booktitle={Interspeech 2015}, author={Chinaev,
    Aleksej and Haeb-Umbach, Reinhold}, year={2015}, pages={1785–1789} }'
  chicago: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “On Optimal Smoothing in Minimum
    Statistics Based Noise Tracking.” In <i>Interspeech 2015</i>, 1785–89, 2015.
  ieee: A. Chinaev and R. Haeb-Umbach, “On Optimal Smoothing in Minimum Statistics
    Based Noise Tracking,” in <i>Interspeech 2015</i>, 2015, pp. 1785–1789.
  mla: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “On Optimal Smoothing in Minimum
    Statistics Based Noise Tracking.” <i>Interspeech 2015</i>, 2015, pp. 1785–89.
  short: 'A. Chinaev, R. Haeb-Umbach, in: Interspeech 2015, 2015, pp. 1785–1789.'
date_created: 2019-07-12T05:27:19Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
keyword:
- speech enhancement
- noise tracking
- optimal smoothing
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/ChHa15.pdf
oa: '1'
page: 1785-1789
publication: Interspeech 2015
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2015/ChHa15_Poster.pdf
status: public
title: On Optimal Smoothing in Minimum Statistics Based Noise Tracking
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11748'
abstract:
- lang: eng
  text: We present a semantic analysis technique for spoken input using Markov Logic
    Networks (MLNs). MLNs combine graphical models with first-order logic. They areparticularly
    suitable for providing inference in the presence of inconsistent and incomplete
    data, which are typical of an automatic speech recognizer's (ASR) output in the
    presence of degraded speech. The target application is a speech interface to a
    home automation system to be operated by people with speech impairments, where
    the ASR output is particularly noisy. In order to cater for dysarthric speech
    with non-canonical phoneme realizations, acoustic representations of the input
    speech are learned in an unsupervised fashion. While training data transcripts
    are not required for the acoustic model training, the MLN training requires supervision,
    however, at a rather loose and abstract level. Results on two databases, one of
    them for dysarthric speech, show that MLN-based semantic analysis clearly outperforms
    baseline approaches employing non-negative matrix factorization, multinomial naive
    Bayes models, or support vector machines.
author:
- first_name: Vladimir
  full_name: Despotovic, Vladimir
  last_name: Despotovic
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Despotovic V, Walter O, Haeb-Umbach R. Semantic Analysis of Spoken Input using
    Markov Logic Networks. In: <i>INTERSPEECH 2015</i>. ; 2015.'
  apa: Despotovic, V., Walter, O., &#38; Haeb-Umbach, R. (2015). Semantic Analysis
    of Spoken Input using Markov Logic Networks. In <i>INTERSPEECH 2015</i>.
  bibtex: '@inproceedings{Despotovic_Walter_Haeb-Umbach_2015, title={Semantic Analysis
    of Spoken Input using Markov Logic Networks}, booktitle={INTERSPEECH 2015}, author={Despotovic,
    Vladimir and Walter, Oliver and Haeb-Umbach, Reinhold}, year={2015} }'
  chicago: Despotovic, Vladimir, Oliver Walter, and Reinhold Haeb-Umbach. “Semantic
    Analysis of Spoken Input Using Markov Logic Networks.” In <i>INTERSPEECH 2015</i>,
    2015.
  ieee: V. Despotovic, O. Walter, and R. Haeb-Umbach, “Semantic Analysis of Spoken
    Input using Markov Logic Networks,” in <i>INTERSPEECH 2015</i>, 2015.
  mla: Despotovic, Vladimir, et al. “Semantic Analysis of Spoken Input Using Markov
    Logic Networks.” <i>INTERSPEECH 2015</i>, 2015.
  short: 'V. Despotovic, O. Walter, R. Haeb-Umbach, in: INTERSPEECH 2015, 2015.'
date_created: 2019-07-12T05:27:30Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/DeWaHa.pdf
oa: '1'
publication: INTERSPEECH 2015
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2015/DeWaHa_Poster.pdf
status: public
title: Semantic Analysis of Spoken Input using Markov Logic Networks
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11755'
abstract:
- lang: eng
  text: This contribution presents a Direction of Arrival (DoA) estimation algorithm
    based on the complex Watson distribution to incorporate both phase and level differences
    of captured micro- phone array signals. The derived algorithm is reviewed in the
    context of the Generalized State Coherence Transform (GSCT) on the one hand and
    a kernel density estimation method on the other hand. A thorough simulative evaluation
    yields insight into parameter selection and provides details on the performance
    for both directional and omni-directional microphones. A comparison to the well
    known Steered Response Power with Phase Transform (SRP-PHAT) algorithm and a state
    of the art DoA estimator which explicitly accounts for aliasing, shows in particular
    the advantages of presented algorithm if inter-sensor level differences are indicative
    of the DoA, as with directional microphones.
author:
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Florian
  full_name: Jacob, Florian
  last_name: Jacob
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Drude L, Jacob F, Haeb-Umbach R. DOA-Estimation based on a Complex Watson
    Kernel Method. In: <i>23th European Signal Processing Conference (EUSIPCO 2015)</i>.
    ; 2015.'
  apa: Drude, L., Jacob, F., &#38; Haeb-Umbach, R. (2015). DOA-Estimation based on
    a Complex Watson Kernel Method. In <i>23th European Signal Processing Conference
    (EUSIPCO 2015)</i>.
  bibtex: '@inproceedings{Drude_Jacob_Haeb-Umbach_2015, title={DOA-Estimation based
    on a Complex Watson Kernel Method}, booktitle={23th European Signal Processing
    Conference (EUSIPCO 2015)}, author={Drude, Lukas and Jacob, Florian and Haeb-Umbach,
    Reinhold}, year={2015} }'
  chicago: Drude, Lukas, Florian Jacob, and Reinhold Haeb-Umbach. “DOA-Estimation
    Based on a Complex Watson Kernel Method.” In <i>23th European Signal Processing
    Conference (EUSIPCO 2015)</i>, 2015.
  ieee: L. Drude, F. Jacob, and R. Haeb-Umbach, “DOA-Estimation based on a Complex
    Watson Kernel Method,” in <i>23th European Signal Processing Conference (EUSIPCO
    2015)</i>, 2015.
  mla: Drude, Lukas, et al. “DOA-Estimation Based on a Complex Watson Kernel Method.”
    <i>23th European Signal Processing Conference (EUSIPCO 2015)</i>, 2015.
  short: 'L. Drude, F. Jacob, R. Haeb-Umbach, in: 23th European Signal Processing
    Conference (EUSIPCO 2015), 2015.'
date_created: 2019-07-12T05:27:38Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/DrJaHa15.pdf
oa: '1'
publication: 23th European Signal Processing Conference (EUSIPCO 2015)
related_material:
  link:
  - description: Presentation
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2015/DrJaHa15_Presentation.pdf
status: public
title: DOA-Estimation based on a Complex Watson Kernel Method
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11810'
author:
- 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: Aleksej
  full_name: Chinaev, Aleksej
  last_name: Chinaev
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Heymann J, Drude L, Chinaev A, Haeb-Umbach R. BLSTM supported GEV Beamformer
    Front-End for the 3RD CHiME Challenge. In: <i>Automatic Speech Recognition and
    Understanding Workshop (ASRU 2015)</i>. ; 2015.'
  apa: Heymann, J., Drude, L., Chinaev, A., &#38; Haeb-Umbach, R. (2015). BLSTM supported
    GEV Beamformer Front-End for the 3RD CHiME Challenge. In <i>Automatic Speech Recognition
    and Understanding Workshop (ASRU 2015)</i>.
  bibtex: '@inproceedings{Heymann_Drude_Chinaev_Haeb-Umbach_2015, title={BLSTM supported
    GEV Beamformer Front-End for the 3RD CHiME Challenge}, booktitle={Automatic Speech
    Recognition and Understanding Workshop (ASRU 2015)}, author={Heymann, Jahn and
    Drude, Lukas and Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2015} }'
  chicago: Heymann, Jahn, Lukas Drude, Aleksej Chinaev, and Reinhold Haeb-Umbach.
    “BLSTM Supported GEV Beamformer Front-End for the 3RD CHiME Challenge.” In <i>Automatic
    Speech Recognition and Understanding Workshop (ASRU 2015)</i>, 2015.
  ieee: J. Heymann, L. Drude, A. Chinaev, and R. Haeb-Umbach, “BLSTM supported GEV
    Beamformer Front-End for the 3RD CHiME Challenge,” in <i>Automatic Speech Recognition
    and Understanding Workshop (ASRU 2015)</i>, 2015.
  mla: Heymann, Jahn, et al. “BLSTM Supported GEV Beamformer Front-End for the 3RD
    CHiME Challenge.” <i>Automatic Speech Recognition and Understanding Workshop (ASRU
    2015)</i>, 2015.
  short: 'J. Heymann, L. Drude, A. Chinaev, R. Haeb-Umbach, in: Automatic Speech Recognition
    and Understanding Workshop (ASRU 2015), 2015.'
date_created: 2019-07-12T05:28:41Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
language:
- iso: eng
publication: Automatic Speech Recognition and Understanding Workshop (ASRU 2015)
status: public
title: BLSTM supported GEV Beamformer Front-End for the 3RD CHiME Challenge
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11813'
abstract:
- lang: eng
  text: 'The parametric Bayesian Feature Enhancement (BFE) and a datadriven Denoising
    Autoencoder (DA) both bring performance gains in severe single-channel speech
    recognition conditions. The first can be adjusted to different conditions by an
    appropriate parameter setting, while the latter needs to be trained on conditions
    similar to the ones expected at decoding time, making it vulnerable to a mismatch
    between training and test conditions. We use a DNN backend and study reverberant
    ASR under three types of mismatch conditions: different room reverberation times,
    different speaker to microphone distances and the difference between artificially
    reverberated data and the recordings in a reverberant environment. We show that
    for these mismatch conditions BFE can provide the targets for a DA. This unsupervised
    adaptation provides a performance gain over the direct use of BFE and even enables
    to compensate for the mismatch of real and simulated reverberant data.'
author:
- 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
- first_name: P.
  full_name: Golik, P.
  last_name: Golik
- first_name: R.
  full_name: Schlueter, R.
  last_name: Schlueter
citation:
  ama: 'Heymann J, Haeb-Umbach R, Golik P, Schlueter R. Unsupervised adaptation of
    a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under
    mismatch conditions. In: <i>Acoustics, Speech and Signal Processing (ICASSP),
    2015 IEEE International Conference On</i>. ; 2015:5053-5057. doi:<a href="https://doi.org/10.1109/ICASSP.2015.7178933">10.1109/ICASSP.2015.7178933</a>'
  apa: Heymann, J., Haeb-Umbach, R., Golik, P., &#38; Schlueter, R. (2015). Unsupervised
    adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant
    asr under mismatch conditions. In <i>Acoustics, Speech and Signal Processing (ICASSP),
    2015 IEEE International Conference on</i> (pp. 5053–5057). <a href="https://doi.org/10.1109/ICASSP.2015.7178933">https://doi.org/10.1109/ICASSP.2015.7178933</a>
  bibtex: '@inproceedings{Heymann_Haeb-Umbach_Golik_Schlueter_2015, title={Unsupervised
    adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant
    asr under mismatch conditions}, DOI={<a href="https://doi.org/10.1109/ICASSP.2015.7178933">10.1109/ICASSP.2015.7178933</a>},
    booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International
    Conference on}, author={Heymann, Jahn and Haeb-Umbach, Reinhold and Golik, P.
    and Schlueter, R.}, year={2015}, pages={5053–5057} }'
  chicago: Heymann, Jahn, Reinhold Haeb-Umbach, P. Golik, and R. Schlueter. “Unsupervised
    Adaptation of a Denoising Autoencoder by Bayesian Feature Enhancement for Reverberant
    Asr under Mismatch Conditions.” In <i>Acoustics, Speech and Signal Processing
    (ICASSP), 2015 IEEE International Conference On</i>, 5053–57, 2015. <a href="https://doi.org/10.1109/ICASSP.2015.7178933">https://doi.org/10.1109/ICASSP.2015.7178933</a>.
  ieee: J. Heymann, R. Haeb-Umbach, P. Golik, and R. Schlueter, “Unsupervised adaptation
    of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr
    under mismatch conditions,” in <i>Acoustics, Speech and Signal Processing (ICASSP),
    2015 IEEE International Conference on</i>, 2015, pp. 5053–5057.
  mla: Heymann, Jahn, et al. “Unsupervised Adaptation of a Denoising Autoencoder by
    Bayesian Feature Enhancement for Reverberant Asr under Mismatch Conditions.” <i>Acoustics,
    Speech and Signal Processing (ICASSP), 2015 IEEE International Conference On</i>,
    2015, pp. 5053–57, doi:<a href="https://doi.org/10.1109/ICASSP.2015.7178933">10.1109/ICASSP.2015.7178933</a>.
  short: 'J. Heymann, R. Haeb-Umbach, P. Golik, R. Schlueter, in: Acoustics, Speech
    and Signal Processing (ICASSP), 2015 IEEE International Conference On, 2015, pp.
    5053–5057.'
date_created: 2019-07-12T05:28:45Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2015.7178933
keyword:
- codecs
- signal denoising
- speech recognition
- Bayesian feature enhancement
- denoising autoencoder
- reverberant ASR
- single-channel speech recognition
- speaker to microphone distances
- unsupervised adaptation
- Adaptation models
- Noise reduction
- Reverberation
- Speech
- Speech recognition
- Training
- deep neuronal networks
- denoising autoencoder
- feature enhancement
- robust speech recognition
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/hey_icassp_2015.pdf
oa: '1'
page: 5053-5057
publication: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International
  Conference on
status: public
title: Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement
  for reverberant asr under mismatch conditions
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11830'
abstract:
- lang: eng
  text: Joint audio-visual speaker tracking requires that the locations of microphones
    and cameras are known and that they are given in a common coordinate system. Sensor
    self-localization algorithms, however, are usually separately developed for either
    the acoustic or the visual modality and return their positions in a modality specific
    coordinate system, often with an unknown rotation, scaling and translation between
    the two. In this paper we propose two techniques to determine the positions of
    acoustic sensors in a common coordinate system, based on audio-visual correlates,
    i.e., events that are localized by both, microphones and cameras separately. The
    first approach maps the output of an acoustic self-calibration algorithm by estimating
    rotation, scale and translation to the visual coordinate system, while the second
    solves a joint system of equations with acoustic and visual directions of arrival
    as input. The evaluation of the two strategies reveals that joint calibration
    outperforms the mapping approach and achieves an overall calibration error of
    0.20m even in reverberant environments.
author:
- first_name: Florian
  full_name: Jacob, Florian
  last_name: Jacob
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Jacob F, Haeb-Umbach R. Absolute Geometry Calibration of Distributed Microphone
    Arrays in an Audio-Visual Sensor Network. <i>ArXiv e-prints</i>. 2015.
  apa: Jacob, F., &#38; Haeb-Umbach, R. (2015). Absolute Geometry Calibration of Distributed
    Microphone Arrays in an Audio-Visual Sensor Network. <i>ArXiv E-Prints</i>.
  bibtex: '@article{Jacob_Haeb-Umbach_2015, title={Absolute Geometry Calibration of
    Distributed Microphone Arrays in an Audio-Visual Sensor Network}, journal={ArXiv
    e-prints}, author={Jacob, Florian and Haeb-Umbach, Reinhold}, year={2015} }'
  chicago: Jacob, Florian, and Reinhold Haeb-Umbach. “Absolute Geometry Calibration
    of Distributed Microphone Arrays in an Audio-Visual Sensor Network.” <i>ArXiv
    E-Prints</i>, 2015.
  ieee: F. Jacob and R. Haeb-Umbach, “Absolute Geometry Calibration of Distributed
    Microphone Arrays in an Audio-Visual Sensor Network,” <i>ArXiv e-prints</i>, 2015.
  mla: Jacob, Florian, and Reinhold Haeb-Umbach. “Absolute Geometry Calibration of
    Distributed Microphone Arrays in an Audio-Visual Sensor Network.” <i>ArXiv E-Prints</i>,
    2015.
  short: F. Jacob, R. Haeb-Umbach, ArXiv E-Prints (2015).
date_created: 2019-07-12T05:29:05Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/JaHa2015.pdf
oa: '1'
publication: ArXiv e-prints
status: public
title: Absolute Geometry Calibration of Distributed Microphone Arrays in an Audio-Visual
  Sensor Network
type: journal_article
user_id: '44006'
year: '2015'
...
---
_id: '11868'
author:
- first_name: Jinyu
  full_name: Li, Jinyu
  last_name: Li
- first_name: Li
  full_name: Deng, Li
  last_name: Deng
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
- first_name: Y.
  full_name: Gong, Y.
  last_name: Gong
citation:
  ama: Li J, Deng L, Haeb-Umbach R, Gong Y. <i>Robust Automatic Speech Recognition</i>.
    Elsevier; 2015.
  apa: Li, J., Deng, L., Haeb-Umbach, R., &#38; Gong, Y. (2015). <i>Robust Automatic
    Speech Recognition</i>. Elsevier.
  bibtex: '@book{Li_Deng_Haeb-Umbach_Gong_2015, title={Robust Automatic Speech Recognition},
    publisher={Elsevier}, author={Li, Jinyu and Deng, Li and Haeb-Umbach, Reinhold
    and Gong, Y.}, year={2015} }'
  chicago: Li, Jinyu, Li Deng, Reinhold Haeb-Umbach, and Y. Gong. <i>Robust Automatic
    Speech Recognition</i>. Elsevier, 2015.
  ieee: J. Li, L. Deng, R. Haeb-Umbach, and Y. Gong, <i>Robust Automatic Speech Recognition</i>.
    Elsevier, 2015.
  mla: Li, Jinyu, et al. <i>Robust Automatic Speech Recognition</i>. Elsevier, 2015.
  short: J. Li, L. Deng, R. Haeb-Umbach, Y. Gong, Robust Automatic Speech Recognition,
    Elsevier, 2015.
date_created: 2019-07-12T05:29:49Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://store.elsevier.com/Robust-Automatic-Speech-Recognition/Jinyu-Li/isbn-9780128023983/
oa: '1'
publisher: Elsevier
related_material:
  link:
  - description: Sample-Chapter
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2015/RASR_Chap5.pdf
  - description: Store
    relation: supplementary_material
    url: http://store.elsevier.com/9780128023983
status: public
title: Robust Automatic Speech Recognition
type: book
user_id: '44006'
year: '2015'
...
---
_id: '11875'
abstract:
- lang: eng
  text: Only a few studies exist on automatic emotion analysis of speech from children
    with Autism Spectrum Conditions (ASC). Out of these, some preliminary studies
    have recently focused on comparing the relevance of selected prosodic features
    against large sets of acoustic, spectral, and cepstral features; however, no study
    so far provided a comparison of performances across different languages. The present
    contribution aims to fill this white spot in the literature and provide insight
    by extensive evaluations carried out on three databases of prompted phrases collected
    in English, Swedish, and Hebrew, inducing nine emotion categories embedded in
    short-stories. The datasets contain speech of children with ASC and typically
    developing children under the same conditions. We evaluate automatic diagnosis
    and recognition of emotions in atypical childrens voice over the nine categories
    including binary valence/arousal discrimination.
author:
- first_name: Erik
  full_name: Marchi, Erik
  last_name: Marchi
- first_name: Bjoern
  full_name: Schuller, Bjoern
  last_name: Schuller
- first_name: Simon
  full_name: Baron-Cohen, Simon
  last_name: Baron-Cohen
- first_name: Ofer
  full_name: Golan, Ofer
  last_name: Golan
- first_name: Sven
  full_name: Boelte, Sven
  last_name: Boelte
- first_name: Prerna
  full_name: Arora, Prerna
  last_name: Arora
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Marchi E, Schuller B, Baron-Cohen S, et al. Typicality and Emotion in the
    Voice of Children with Autism Spectrum Condition: Evidence Across Three Languages.
    In: <i>INTERSPEECH 2015</i>. ; 2015.'
  apa: 'Marchi, E., Schuller, B., Baron-Cohen, S., Golan, O., Boelte, S., Arora, P.,
    &#38; Haeb-Umbach, R. (2015). Typicality and Emotion in the Voice of Children
    with Autism Spectrum Condition: Evidence Across Three Languages. In <i>INTERSPEECH
    2015</i>.'
  bibtex: '@inproceedings{Marchi_Schuller_Baron-Cohen_Golan_Boelte_Arora_Haeb-Umbach_2015,
    title={Typicality and Emotion in the Voice of Children with Autism Spectrum Condition:
    Evidence Across Three Languages}, booktitle={INTERSPEECH 2015}, author={Marchi,
    Erik and Schuller, Bjoern and Baron-Cohen, Simon and Golan, Ofer and Boelte, Sven
    and Arora, Prerna and Haeb-Umbach, Reinhold}, year={2015} }'
  chicago: 'Marchi, Erik, Bjoern Schuller, Simon Baron-Cohen, Ofer Golan, Sven Boelte,
    Prerna Arora, and Reinhold Haeb-Umbach. “Typicality and Emotion in the Voice of
    Children with Autism Spectrum Condition: Evidence Across Three Languages.” In
    <i>INTERSPEECH 2015</i>, 2015.'
  ieee: 'E. Marchi <i>et al.</i>, “Typicality and Emotion in the Voice of Children
    with Autism Spectrum Condition: Evidence Across Three Languages,” in <i>INTERSPEECH
    2015</i>, 2015.'
  mla: 'Marchi, Erik, et al. “Typicality and Emotion in the Voice of Children with
    Autism Spectrum Condition: Evidence Across Three Languages.” <i>INTERSPEECH 2015</i>,
    2015.'
  short: 'E. Marchi, B. Schuller, S. Baron-Cohen, O. Golan, S. Boelte, P. Arora, R.
    Haeb-Umbach, in: INTERSPEECH 2015, 2015.'
date_created: 2019-07-12T05:29:57Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/MaScBaOfSvPrHa.pdf
oa: '1'
publication: INTERSPEECH 2015
status: public
title: 'Typicality and Emotion in the Voice of Children with Autism Spectrum Condition:
  Evidence Across Three Languages'
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11919'
abstract:
- lang: eng
  text: In this paper we present a source counting algorithm to determine the number
    of speakers in a speech mixture. In our proposed method, we model the histogram
    of estimated directions of arrival with a nonparametric Bayesian infinite Gaussian
    mixture model. As an alternative to classical model selection criteria and to
    avoid specifying the maximum number of mixture components in advance, a Dirichlet
    process prior is employed over the mixture components. This allows to automatically
    determine the optimal number of mixture components that most probably model the
    observations. We demonstrate by experiments that this model outperforms a parametric
    approach using a finite Gaussian mixture model with a Dirichlet distribution prior
    over the mixture weights.
author:
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Lukas
  full_name: Drude, Lukas
  id: '11213'
  last_name: Drude
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Walter O, Drude L, Haeb-Umbach R. Source Counting in Speech Mixtures by Nonparametric
    Bayesian Estimation of an infinite Gaussian Mixture Model. In: <i>40th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2015)</i>. ; 2015.'
  apa: Walter, O., Drude, L., &#38; Haeb-Umbach, R. (2015). Source Counting in Speech
    Mixtures by Nonparametric Bayesian Estimation of an infinite Gaussian Mixture
    Model. In <i>40th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2015)</i>.
  bibtex: '@inproceedings{Walter_Drude_Haeb-Umbach_2015, title={Source Counting in
    Speech Mixtures by Nonparametric Bayesian Estimation of an infinite Gaussian Mixture
    Model}, booktitle={40th International Conference on Acoustics, Speech and Signal
    Processing (ICASSP 2015)}, author={Walter, Oliver and Drude, Lukas and Haeb-Umbach,
    Reinhold}, year={2015} }'
  chicago: Walter, Oliver, Lukas Drude, and Reinhold Haeb-Umbach. “Source Counting
    in Speech Mixtures by Nonparametric Bayesian Estimation of an Infinite Gaussian
    Mixture Model.” In <i>40th International Conference on Acoustics, Speech and Signal
    Processing (ICASSP 2015)</i>, 2015.
  ieee: O. Walter, L. Drude, and R. Haeb-Umbach, “Source Counting in Speech Mixtures
    by Nonparametric Bayesian Estimation of an infinite Gaussian Mixture Model,” in
    <i>40th International Conference on Acoustics, Speech and Signal Processing (ICASSP
    2015)</i>, 2015.
  mla: Walter, Oliver, et al. “Source Counting in Speech Mixtures by Nonparametric
    Bayesian Estimation of an Infinite Gaussian Mixture Model.” <i>40th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2015)</i>, 2015.
  short: 'O. Walter, L. Drude, R. Haeb-Umbach, in: 40th International Conference on
    Acoustics, Speech and Signal Processing (ICASSP 2015), 2015.'
date_created: 2019-07-12T05:30:47Z
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/2015/WaDrHa15.pdf
oa: '1'
publication: 40th International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2015)
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2015/WaDrHa15_Poster.pdf
status: public
title: Source Counting in Speech Mixtures by Nonparametric Bayesian Estimation of
  an infinite Gaussian Mixture Model
type: conference
user_id: '44006'
year: '2015'
...
---
_id: '11922'
abstract:
- lang: eng
  text: 'Besides the core learning algorithm itself, one major question in machine
    learning is how to best encode given training data such that the learning technology
    can efficiently learn based thereon and generalize to novel data. While classical
    approaches often rely on a hand coded data representation, the topic of autonomous
    representation or feature learning plays a major role in modern learning architectures.
    The goal of this contribution is to give an overview about different principles
    of autonomous feature learning, and to exemplify two principles based on two recent
    examples: autonomous metric learning for sequences, and autonomous learning of
    a deep representation for spoken language, respectively.'
author:
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
- first_name: Bassam
  full_name: Mokbel, Bassam
  last_name: Mokbel
- first_name: Benjamin
  full_name: Paassen, Benjamin
  last_name: Paassen
- first_name: Barbara
  full_name: Hammer, Barbara
  last_name: Hammer
citation:
  ama: Walter O, Haeb-Umbach R, Mokbel B, Paassen B, Hammer B. Autonomous Learning
    of Representations. <i>KI - Kuenstliche Intelligenz</i>. 2015:1-13. doi:<a href="http://dx.doi.org/10.1007/s13218-015-0372-1">http://dx.doi.org/10.1007/s13218-015-0372-1</a>
  apa: Walter, O., Haeb-Umbach, R., Mokbel, B., Paassen, B., &#38; Hammer, B. (2015).
    Autonomous Learning of Representations. <i>KI - Kuenstliche Intelligenz</i>, 1–13.
    <a href="http://dx.doi.org/10.1007/s13218-015-0372-1">http://dx.doi.org/10.1007/s13218-015-0372-1</a>
  bibtex: '@article{Walter_Haeb-Umbach_Mokbel_Paassen_Hammer_2015, title={Autonomous
    Learning of Representations}, DOI={<a href="http://dx.doi.org/10.1007/s13218-015-0372-1">http://dx.doi.org/10.1007/s13218-015-0372-1</a>},
    journal={KI - Kuenstliche Intelligenz}, author={Walter, Oliver and Haeb-Umbach,
    Reinhold and Mokbel, Bassam and Paassen, Benjamin and Hammer, Barbara}, year={2015},
    pages={1–13} }'
  chicago: Walter, Oliver, Reinhold Haeb-Umbach, Bassam Mokbel, Benjamin Paassen,
    and Barbara Hammer. “Autonomous Learning of Representations.” <i>KI - Kuenstliche
    Intelligenz</i>, 2015, 1–13. <a href="http://dx.doi.org/10.1007/s13218-015-0372-1">http://dx.doi.org/10.1007/s13218-015-0372-1</a>.
  ieee: O. Walter, R. Haeb-Umbach, B. Mokbel, B. Paassen, and B. Hammer, “Autonomous
    Learning of Representations,” <i>KI - Kuenstliche Intelligenz</i>, pp. 1–13, 2015.
  mla: Walter, Oliver, et al. “Autonomous Learning of Representations.” <i>KI - Kuenstliche
    Intelligenz</i>, 2015, pp. 1–13, doi:<a href="http://dx.doi.org/10.1007/s13218-015-0372-1">http://dx.doi.org/10.1007/s13218-015-0372-1</a>.
  short: O. Walter, R. Haeb-Umbach, B. Mokbel, B. Paassen, B. Hammer, KI - Kuenstliche
    Intelligenz (2015) 1–13.
date_created: 2019-07-12T05:30:51Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: http://dx.doi.org/10.1007/s13218-015-0372-1
keyword:
- Representation learning
- Metric learning
- Deep representation
- Spoken language
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2015/WaHaMoPaHa15.pdf
oa: '1'
page: 1-13
publication: KI - Kuenstliche Intelligenz
status: public
title: Autonomous Learning of Representations
type: journal_article
user_id: '44006'
year: '2015'
...
---
_id: '11923'
abstract:
- lang: eng
  text: 'In this paper we show that recently developed algorithms for unsupervised
    word segmentation can be a valuable tool for the documentation of endangered languages.
    We applied an unsupervised word segmentation algorithm based on a nested Pitman-Yor
    language model to two austronesian languages, Wooi and Waima''a. The algorithm
    was then modified and parameterized to cater the needs of linguists for high precision
    of lexical discovery: We obtained a lexicon precision of of 69.2\% and 67.5\%
    for Wooi and Waima''a, respectively, if single-letter words and words found less
    than three times were discarded. A comparison with an English word segmentation
    task showed comparable performance, verifying that the assumptions underlying
    the Pitman-Yor language model, the universality of Zipf''s law and the power of
    n-gram structures, do also hold for languages as exotic as Wooi and Waima''a.'
author:
- first_name: Oliver
  full_name: Walter, Oliver
  last_name: Walter
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
- first_name: Jan
  full_name: Strunk, Jan
  last_name: Strunk
- first_name: 'Nikolaus '
  full_name: 'P. Himmelmann, Nikolaus '
  last_name: P. Himmelmann
citation:
  ama: Walter O, Haeb-Umbach R, Strunk J, P. Himmelmann N. <i>Lexicon Discovery for
    Language Preservation Using Unsupervised Word Segmentation with Pitman-Yor Language
    Models (FGNT-2015-01)</i>.; 2015.
  apa: Walter, O., Haeb-Umbach, R., Strunk, J., &#38; P. Himmelmann, N. (2015). <i>Lexicon
    Discovery for Language Preservation using Unsupervised Word Segmentation with
    Pitman-Yor Language Models (FGNT-2015-01)</i>.
  bibtex: '@book{Walter_Haeb-Umbach_Strunk_P. Himmelmann_2015, title={Lexicon Discovery
    for Language Preservation using Unsupervised Word Segmentation with Pitman-Yor
    Language Models (FGNT-2015-01)}, author={Walter, Oliver and Haeb-Umbach, Reinhold
    and Strunk, Jan and P. Himmelmann, Nikolaus }, year={2015} }'
  chicago: Walter, Oliver, Reinhold Haeb-Umbach, Jan Strunk, and Nikolaus  P. Himmelmann.
    <i>Lexicon Discovery for Language Preservation Using Unsupervised Word Segmentation
    with Pitman-Yor Language Models (FGNT-2015-01)</i>, 2015.
  ieee: O. Walter, R. Haeb-Umbach, J. Strunk, and N. P. Himmelmann, <i>Lexicon Discovery
    for Language Preservation using Unsupervised Word Segmentation with Pitman-Yor
    Language Models (FGNT-2015-01)</i>. 2015.
  mla: Walter, Oliver, et al. <i>Lexicon Discovery for Language Preservation Using
    Unsupervised Word Segmentation with Pitman-Yor Language Models (FGNT-2015-01)</i>.
    2015.
  short: O. Walter, R. Haeb-Umbach, J. Strunk, N. P. Himmelmann, Lexicon Discovery
    for Language Preservation Using Unsupervised Word Segmentation with Pitman-Yor
    Language Models (FGNT-2015-01), 2015.
date_created: 2019-07-12T05:30:52Z
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/2015/WaHaStHi.pdf
oa: '1'
status: public
title: Lexicon Discovery for Language Preservation using Unsupervised Word Segmentation
  with Pitman-Yor Language Models (FGNT-2015-01)
type: report
user_id: '44006'
year: '2015'
...