---
_id: '11716'
abstract:
- lang: eng
  text: The accuracy of automatic speech recognition systems in noisy and reverberant
    environments can be improved notably by exploiting the uncertainty of the estimated
    speech features using so-called uncertainty-of-observation techniques. In this
    paper, we introduce a new Bayesian decision rule that can serve as a mathematical
    framework from which both known and new uncertainty-of-observation techniques
    can be either derived or approximated. The new decision rule in its direct form
    leads to the new significance decoding approach for Gaussian mixture models, which
    results in better performance compared to standard uncertainty-of-observation
    techniques in different additive and convolutive noise scenarios.
author:
- first_name: Ahmed H.
  full_name: Abdelaziz, Ahmed H.
  last_name: Abdelaziz
- first_name: Steffen
  full_name: Zeiler, Steffen
  last_name: Zeiler
- first_name: Dorothea
  full_name: Kolossa, Dorothea
  last_name: Kolossa
- first_name: Volker
  full_name: Leutnant, Volker
  last_name: Leutnant
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Abdelaziz AH, Zeiler S, Kolossa D, Leutnant V, Haeb-Umbach R. GMM-based significance
    decoding. In: <i>Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International
    Conference On</i>. ; 2013:6827-6831. doi:<a href="https://doi.org/10.1109/ICASSP.2013.6638984">10.1109/ICASSP.2013.6638984</a>'
  apa: Abdelaziz, A. H., Zeiler, S., Kolossa, D., Leutnant, V., &#38; Haeb-Umbach,
    R. (2013). GMM-based significance decoding. In <i>Acoustics, Speech and Signal
    Processing (ICASSP), 2013 IEEE International Conference on</i> (pp. 6827–6831).
    <a href="https://doi.org/10.1109/ICASSP.2013.6638984">https://doi.org/10.1109/ICASSP.2013.6638984</a>
  bibtex: '@inproceedings{Abdelaziz_Zeiler_Kolossa_Leutnant_Haeb-Umbach_2013, title={GMM-based
    significance decoding}, DOI={<a href="https://doi.org/10.1109/ICASSP.2013.6638984">10.1109/ICASSP.2013.6638984</a>},
    booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International
    Conference on}, author={Abdelaziz, Ahmed H. and Zeiler, Steffen and Kolossa, Dorothea
    and Leutnant, Volker and Haeb-Umbach, Reinhold}, year={2013}, pages={6827–6831}
    }'
  chicago: Abdelaziz, Ahmed H., Steffen Zeiler, Dorothea Kolossa, Volker Leutnant,
    and Reinhold Haeb-Umbach. “GMM-Based Significance Decoding.” In <i>Acoustics,
    Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On</i>,
    6827–31, 2013. <a href="https://doi.org/10.1109/ICASSP.2013.6638984">https://doi.org/10.1109/ICASSP.2013.6638984</a>.
  ieee: A. H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, and R. Haeb-Umbach, “GMM-based
    significance decoding,” in <i>Acoustics, Speech and Signal Processing (ICASSP),
    2013 IEEE International Conference on</i>, 2013, pp. 6827–6831.
  mla: Abdelaziz, Ahmed H., et al. “GMM-Based Significance Decoding.” <i>Acoustics,
    Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On</i>,
    2013, pp. 6827–31, doi:<a href="https://doi.org/10.1109/ICASSP.2013.6638984">10.1109/ICASSP.2013.6638984</a>.
  short: 'A.H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, R. Haeb-Umbach, in:
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference
    On, 2013, pp. 6827–6831.'
date_created: 2019-07-12T05:26:53Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638984
keyword:
- Bayes methods
- Gaussian processes
- convolution
- decision theory
- decoding
- noise
- reverberation
- speech coding
- speech recognition
- Bayesian decision rule
- GMM
- Gaussian mixture models
- additive noise scenarios
- automatic speech recognition systems
- convolutive noise scenarios
- decoding approach
- mathematical framework
- reverberant environments
- significance decoding
- speech feature estimation
- uncertainty-of-observation techniques
- Hidden Markov models
- Maximum likelihood decoding
- Noise
- Speech
- Speech recognition
- Uncertainty
- Uncertainty-of-observation
- modified imputation
- noise robust speech recognition
- significance decoding
- uncertainty decoding
language:
- iso: eng
page: 6827-6831
publication: Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International
  Conference on
publication_identifier:
  issn:
  - 1520-6149
status: public
title: GMM-based significance decoding
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11740'
abstract:
- lang: eng
  text: In this contribution we derive the Maximum A-Posteriori (MAP) estimates of
    the parameters of a Gaussian Mixture Model (GMM) in the presence of noisy observations.
    We assume the distortion to be white Gaussian noise of known mean and variance.
    An approximate conjugate prior of the GMM parameters is derived allowing for a
    computationally efficient implementation in a sequential estimation framework.
    Simulations on artificially generated data demonstrate the superiority of the
    proposed method compared to the Maximum Likelihood technique and to the ordinary
    MAP approach, whose estimates are corrected by the known statistics of the distortion
    in a straightforward manner.
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. MAP-based Estimation of the Parameters of a Gaussian
    Mixture Model in the Presence of Noisy Observations. In: <i>38th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>. ; 2013:3352-3356.
    doi:<a href="https://doi.org/10.1109/ICASSP.2013.6638279">10.1109/ICASSP.2013.6638279</a>'
  apa: Chinaev, A., &#38; Haeb-Umbach, R. (2013). MAP-based Estimation of the Parameters
    of a Gaussian Mixture Model in the Presence of Noisy Observations. In <i>38th
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>
    (pp. 3352–3356). <a href="https://doi.org/10.1109/ICASSP.2013.6638279">https://doi.org/10.1109/ICASSP.2013.6638279</a>
  bibtex: '@inproceedings{Chinaev_Haeb-Umbach_2013, title={MAP-based Estimation of
    the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations},
    DOI={<a href="https://doi.org/10.1109/ICASSP.2013.6638279">10.1109/ICASSP.2013.6638279</a>},
    booktitle={38th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2013)}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2013},
    pages={3352–3356} }'
  chicago: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the
    Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.”
    In <i>38th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2013)</i>, 3352–56, 2013. <a href="https://doi.org/10.1109/ICASSP.2013.6638279">https://doi.org/10.1109/ICASSP.2013.6638279</a>.
  ieee: A. Chinaev and R. Haeb-Umbach, “MAP-based Estimation of the Parameters of
    a Gaussian Mixture Model in the Presence of Noisy Observations,” in <i>38th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013,
    pp. 3352–3356.
  mla: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters
    of a Gaussian Mixture Model in the Presence of Noisy Observations.” <i>38th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013,
    pp. 3352–56, doi:<a href="https://doi.org/10.1109/ICASSP.2013.6638279">10.1109/ICASSP.2013.6638279</a>.
  short: 'A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.'
date_created: 2019-07-12T05:27:20Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638279
keyword:
- Gaussian noise
- maximum likelihood estimation
- parameter estimation
- GMM parameter
- Gaussian mixture model
- MAP estimation
- Map-based estimation
- maximum a-posteriori estimation
- maximum likelihood technique
- noisy observation
- sequential estimation framework
- white Gaussian noise
- Additive noise
- Gaussian mixture model
- Maximum likelihood estimation
- Noise measurement
- Gaussian mixture model
- Maximum a posteriori estimation
- Maximum likelihood estimation
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13.pdf
oa: '1'
page: 3352-3356
publication: 38th International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2013)
publication_identifier:
  issn:
  - 1520-6149
related_material:
  link:
  - description: Poster
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13_Poster.pdf
status: public
title: MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence
  of Noisy Observations
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11883'
abstract:
- lang: eng
  text: In this paper, we experimentally evaluate algorithms for velocity estimation
    of a GSM 900 mobile terminal which are based on the analysis of the statistical
    properties of the fast fading process. It is shown how theses statistics can be
    obtained from the training sequences present in downlink transmission bursts without
    establishing an active connection. Realistic simulations of a GSM channel according
    to the COST 207 channel models have been conducted. These models incorporate effects
    like multipath propagation, fading, cochannel interference and additive noise.
    It is shown that velocity estimation by searching for the maximum slope of the
    power density spectrum of the fast fading performs best.
author:
- first_name: Sven
  full_name: Peschke, Sven
  last_name: Peschke
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Peschke S, Haeb-Umbach R. Velocity Estimation of Mobile Terminals by Exploiting
    GSM Downlink Signalling. In: <i>4th Workshop on Positioning Navigation and Communication
    (WPNC 2007)</i>. ; 2007:217-222. doi:<a href="https://doi.org/10.1109/WPNC.2007.353637">10.1109/WPNC.2007.353637</a>'
  apa: Peschke, S., &#38; Haeb-Umbach, R. (2007). Velocity Estimation of Mobile Terminals
    by Exploiting GSM Downlink Signalling. In <i>4th Workshop on Positioning Navigation
    and Communication (WPNC 2007)</i> (pp. 217–222). <a href="https://doi.org/10.1109/WPNC.2007.353637">https://doi.org/10.1109/WPNC.2007.353637</a>
  bibtex: '@inproceedings{Peschke_Haeb-Umbach_2007, title={Velocity Estimation of
    Mobile Terminals by Exploiting GSM Downlink Signalling}, DOI={<a href="https://doi.org/10.1109/WPNC.2007.353637">10.1109/WPNC.2007.353637</a>},
    booktitle={4th Workshop on Positioning Navigation and Communication (WPNC 2007)},
    author={Peschke, Sven and Haeb-Umbach, Reinhold}, year={2007}, pages={217–222}
    }'
  chicago: Peschke, Sven, and Reinhold Haeb-Umbach. “Velocity Estimation of Mobile
    Terminals by Exploiting GSM Downlink Signalling.” In <i>4th Workshop on Positioning
    Navigation and Communication (WPNC 2007)</i>, 217–22, 2007. <a href="https://doi.org/10.1109/WPNC.2007.353637">https://doi.org/10.1109/WPNC.2007.353637</a>.
  ieee: S. Peschke and R. Haeb-Umbach, “Velocity Estimation of Mobile Terminals by
    Exploiting GSM Downlink Signalling,” in <i>4th Workshop on Positioning Navigation
    and Communication (WPNC 2007)</i>, 2007, pp. 217–222.
  mla: Peschke, Sven, and Reinhold Haeb-Umbach. “Velocity Estimation of Mobile Terminals
    by Exploiting GSM Downlink Signalling.” <i>4th Workshop on Positioning Navigation
    and Communication (WPNC 2007)</i>, 2007, pp. 217–22, doi:<a href="https://doi.org/10.1109/WPNC.2007.353637">10.1109/WPNC.2007.353637</a>.
  short: 'S. Peschke, R. Haeb-Umbach, in: 4th Workshop on Positioning Navigation and
    Communication (WPNC 2007), 2007, pp. 217–222.'
date_created: 2019-07-12T05:30:06Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/WPNC.2007.353637
keyword:
- additive noise
- cellular radio
- channel estimation
- cochannel interference
- COST 207 channel models
- downlink transmission bursts
- fading channels
- fading process
- GSM downlink signalling
- mobile terminals
- multipath channels
- multipath propagation
- power density spectrum
- statistical analysis
- statistical properties
- telecommunication links
- telecommunication terminals
- velocity estimation
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2007/PeHa07.pdf
oa: '1'
page: 217-222
publication: 4th Workshop on Positioning Navigation and Communication (WPNC 2007)
status: public
title: Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling
type: conference
user_id: '44006'
year: '2007'
...