---
_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: '11745'
abstract:
- lang: eng
  text: In this paper we present a novel noise power spectral density tracking algorithm
    and its use in single-channel speech enhancement. It has the unique feature that
    it is able to track the noise statistics even if speech is dominant in a given
    time-frequency bin. As a consequence it can follow non-stationary noise superposed
    by speech, even in the critical case of rising noise power. The algorithm requires
    an initial estimate of the power spectrum of speech and is thus meant to be used
    as a postprocessor to a first speech enhancement stage. An experimental comparison
    with a state-of-the-art noise tracking algorithm demonstrates lower estimation
    errors under low SNR conditions and smaller fluctuations of the estimated values,
    resulting in improved speech quality as measured by PESQ scores.
author:
- first_name: Aleksej
  full_name: Chinaev, Aleksej
  last_name: Chinaev
- first_name: Alexander
  full_name: Krueger, Alexander
  last_name: Krueger
- 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: 'Chinaev A, Krueger A, Tran Vu DH, Haeb-Umbach R. Improved Noise Power Spectral
    Density Tracking by a MAP-based Postprocessor. In: <i>37th International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>. ; 2012.'
  apa: Chinaev, A., Krueger, A., Tran Vu, D. H., &#38; Haeb-Umbach, R. (2012). Improved
    Noise Power Spectral Density Tracking by a MAP-based Postprocessor. In <i>37th
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>.
  bibtex: '@inproceedings{Chinaev_Krueger_Tran Vu_Haeb-Umbach_2012, title={Improved
    Noise Power Spectral Density Tracking by a MAP-based Postprocessor}, booktitle={37th
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)},
    author={Chinaev, Aleksej and Krueger, Alexander and Tran Vu, Dang Hai and Haeb-Umbach,
    Reinhold}, year={2012} }'
  chicago: Chinaev, Aleksej, Alexander Krueger, Dang Hai Tran Vu, and Reinhold Haeb-Umbach.
    “Improved Noise Power Spectral Density Tracking by a MAP-Based Postprocessor.”
    In <i>37th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2012)</i>, 2012.
  ieee: A. Chinaev, A. Krueger, D. H. Tran Vu, and R. Haeb-Umbach, “Improved Noise
    Power Spectral Density Tracking by a MAP-based Postprocessor,” in <i>37th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>, 2012.
  mla: Chinaev, Aleksej, et al. “Improved Noise Power Spectral Density Tracking by
    a MAP-Based Postprocessor.” <i>37th International Conference on Acoustics, Speech
    and Signal Processing (ICASSP 2012)</i>, 2012.
  short: 'A. Chinaev, A. Krueger, D.H. Tran Vu, R. Haeb-Umbach, in: 37th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.'
date_created: 2019-07-12T05:27:26Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
keyword:
- MAP parameter estimation
- noise power estimation
- speech enhancement
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12.pdf
oa: '1'
publication: 37th International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2012)
related_material:
  link:
  - description: Presentation
    relation: supplementary_material
    url: https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12_Talk.pdf
status: public
title: Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor
type: conference
user_id: '44006'
year: '2012'
...
---
_id: '11850'
abstract:
- lang: eng
  text: In this paper, we present a novel blocking matrix and fixed beamformer design
    for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure.
    They are based on a new method for estimating the acoustical transfer function
    ratios in the presence of stationary noise. The estimation method relies on solving
    a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector
    tracking utilizing the power iteration method is employed and shown to achieve
    a high convergence speed. Simulation results demonstrate that the proposed beamformer
    leads to better noise and interference reduction and reduced speech distortions
    compared to other blocking matrix designs from the literature.
author:
- first_name: Alexander
  full_name: Krueger, Alexander
  last_name: Krueger
- first_name: Ernst
  full_name: Warsitz, Ernst
  last_name: Warsitz
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Krueger A, Warsitz E, Haeb-Umbach R. Speech Enhancement With a GSC-Like Structure
    Employing Eigenvector-Based Transfer Function Ratios Estimation. <i>IEEE Transactions
    on Audio, Speech, and Language Processing</i>. 2011;19(1):206-219. doi:<a href="https://doi.org/10.1109/TASL.2010.2047324">10.1109/TASL.2010.2047324</a>
  apa: Krueger, A., Warsitz, E., &#38; Haeb-Umbach, R. (2011). Speech Enhancement
    With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios
    Estimation. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>,
    <i>19</i>(1), 206–219. <a href="https://doi.org/10.1109/TASL.2010.2047324">https://doi.org/10.1109/TASL.2010.2047324</a>
  bibtex: '@article{Krueger_Warsitz_Haeb-Umbach_2011, title={Speech Enhancement With
    a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation},
    volume={19}, DOI={<a href="https://doi.org/10.1109/TASL.2010.2047324">10.1109/TASL.2010.2047324</a>},
    number={1}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
    author={Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2011},
    pages={206–219} }'
  chicago: 'Krueger, Alexander, Ernst Warsitz, and Reinhold Haeb-Umbach. “Speech Enhancement
    With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios
    Estimation.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>
    19, no. 1 (2011): 206–19. <a href="https://doi.org/10.1109/TASL.2010.2047324">https://doi.org/10.1109/TASL.2010.2047324</a>.'
  ieee: A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like
    Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” <i>IEEE
    Transactions on Audio, Speech, and Language Processing</i>, vol. 19, no. 1, pp.
    206–219, 2011.
  mla: Krueger, Alexander, et al. “Speech Enhancement With a GSC-Like Structure Employing
    Eigenvector-Based Transfer Function Ratios Estimation.” <i>IEEE Transactions on
    Audio, Speech, and Language Processing</i>, vol. 19, no. 1, 2011, pp. 206–19,
    doi:<a href="https://doi.org/10.1109/TASL.2010.2047324">10.1109/TASL.2010.2047324</a>.
  short: A. Krueger, E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech,
    and Language Processing 19 (2011) 206–219.
date_created: 2019-07-12T05:29:28Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASL.2010.2047324
intvolume: '        19'
issue: '1'
keyword:
- acoustical transfer function ratio
- adaptive eigenvector tracking
- array signal processing
- beamformer design
- blocking matrix
- eigenvalues and eigenfunctions
- eigenvector-based transfer function ratios estimation
- generalized sidelobe canceler
- interference reduction
- iterative methods
- power iteration method
- reduced speech distortions
- reverberant enclosure
- reverberation
- speech enhancement
- stationary noise
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2011/KrWaHa11.pdf
oa: '1'
page: 206-219
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer
  Function Ratios Estimation
type: journal_article
user_id: '44006'
volume: 19
year: '2011'
...
---
_id: '11913'
abstract:
- lang: eng
  text: In this paper we propose to employ directional statistics in a complex vector
    space to approach the problem of blind speech separation in the presence of spatially
    correlated noise. We interpret the values of the short time Fourier transform
    of the microphone signals to be draws from a mixture of complex Watson distributions,
    a probabilistic model which naturally accounts for spatial aliasing. The parameters
    of the density are related to the a priori source probabilities, the power of
    the sources and the transfer function ratios from sources to sensors. Estimation
    formulas are derived for these parameters by employing the Expectation Maximization
    (EM) algorithm. The E-step corresponds to the estimation of the source presence
    probabilities for each time-frequency bin, while the M-step leads to a maximum
    signal-to-noise ratio (MaxSNR) beamformer in the presence of uncertainty about
    the source activity. Experimental results are reported for an implementation in
    a generalized sidelobe canceller (GSC) like spatial beamforming configuration
    for 3 speech sources with significant coherent noise in reverberant environments,
    demonstrating the usefulness of the novel modeling framework.
author:
- 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: 'Tran Vu DH, Haeb-Umbach R. Blind speech separation employing directional statistics
    in an Expectation Maximization framework. In: <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>. ; 2010:241-244.
    doi:<a href="https://doi.org/10.1109/ICASSP.2010.5495994">10.1109/ICASSP.2010.5495994</a>'
  apa: Tran Vu, D. H., &#38; Haeb-Umbach, R. (2010). Blind speech separation employing
    directional statistics in an Expectation Maximization framework. In <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i> (pp. 241–244).
    <a href="https://doi.org/10.1109/ICASSP.2010.5495994">https://doi.org/10.1109/ICASSP.2010.5495994</a>
  bibtex: '@inproceedings{Tran Vu_Haeb-Umbach_2010, title={Blind speech separation
    employing directional statistics in an Expectation Maximization framework}, DOI={<a
    href="https://doi.org/10.1109/ICASSP.2010.5495994">10.1109/ICASSP.2010.5495994</a>},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2010)}, author={Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2010},
    pages={241–244} }'
  chicago: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
    Directional Statistics in an Expectation Maximization Framework.” In <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 241–44,
    2010. <a href="https://doi.org/10.1109/ICASSP.2010.5495994">https://doi.org/10.1109/ICASSP.2010.5495994</a>.
  ieee: D. H. Tran Vu and R. Haeb-Umbach, “Blind speech separation employing directional
    statistics in an Expectation Maximization framework,” in <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 2010,
    pp. 241–244.
  mla: Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing
    Directional Statistics in an Expectation Maximization Framework.” <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 2010,
    pp. 241–44, doi:<a href="https://doi.org/10.1109/ICASSP.2010.5495994">10.1109/ICASSP.2010.5495994</a>.
  short: 'D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.'
date_created: 2019-07-12T05:30:40Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2010.5495994
keyword:
- array signal processing
- blind source separation
- blind speech separation
- complex vector space
- complex Watson distribution
- directional statistics
- expectation-maximisation algorithm
- expectation maximization algorithm
- Fourier transform
- Fourier transforms
- generalized sidelobe canceller
- interference suppression
- maximum signal-to-noise ratio beamformer
- microphone signal
- probabilistic model
- spatial aliasing
- spatial beamforming configuration
- speech enhancement
- statistical distributions
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-2.pdf
oa: '1'
page: 241-244
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2010)
status: public
title: Blind speech separation employing directional statistics in an Expectation
  Maximization framework
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '11937'
abstract:
- lang: eng
  text: In automatic speech recognition, hidden Markov models (HMMs) are commonly
    used for speech decoding, while switching linear dynamic models (SLDMs) can be
    employed for a preceding model-based speech feature enhancement. In this paper,
    these model types are combined in order to obtain a novel iterative speech feature
    enhancement and recognition architecture. It is shown that speech feature enhancement
    with SLDMs can be improved by feeding back information from the HMM to the enhancement
    stage. Two different feedback structures are derived. In the first, the posteriors
    of the HMM states are used to control the model probabilities of the SLDMs, while
    in the second they are employed to directly influence the estimate of the speech
    feature distribution. Both approaches lead to improvements in recognition accuracy
    both on the AURORA2 and AURORA4 databases compared to non-iterative speech feature
    enhancement with SLDMs. It is also shown that a combination with uncertainty decoding
    further enhances performance.
author:
- first_name: Stefan
  full_name: Windmann, Stefan
  last_name: Windmann
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: Windmann S, Haeb-Umbach R. Approaches to Iterative Speech Feature Enhancement
    and Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>.
    2009;17(5):974-984. doi:<a href="https://doi.org/10.1109/TASL.2009.2014894">10.1109/TASL.2009.2014894</a>
  apa: Windmann, S., &#38; Haeb-Umbach, R. (2009). Approaches to Iterative Speech
    Feature Enhancement and Recognition. <i>IEEE Transactions on Audio, Speech, and
    Language Processing</i>, <i>17</i>(5), 974–984. <a href="https://doi.org/10.1109/TASL.2009.2014894">https://doi.org/10.1109/TASL.2009.2014894</a>
  bibtex: '@article{Windmann_Haeb-Umbach_2009, title={Approaches to Iterative Speech
    Feature Enhancement and Recognition}, volume={17}, DOI={<a href="https://doi.org/10.1109/TASL.2009.2014894">10.1109/TASL.2009.2014894</a>},
    number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
    author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={974–984}
    }'
  chicago: 'Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech
    Feature Enhancement and Recognition.” <i>IEEE Transactions on Audio, Speech, and
    Language Processing</i> 17, no. 5 (2009): 974–84. <a href="https://doi.org/10.1109/TASL.2009.2014894">https://doi.org/10.1109/TASL.2009.2014894</a>.'
  ieee: S. Windmann and R. Haeb-Umbach, “Approaches to Iterative Speech Feature Enhancement
    and Recognition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>,
    vol. 17, no. 5, pp. 974–984, 2009.
  mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech
    Feature Enhancement and Recognition.” <i>IEEE Transactions on Audio, Speech, and
    Language Processing</i>, vol. 17, no. 5, 2009, pp. 974–84, doi:<a href="https://doi.org/10.1109/TASL.2009.2014894">10.1109/TASL.2009.2014894</a>.
  short: S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
    Processing 17 (2009) 974–984.
date_created: 2019-07-12T05:31:08Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/TASL.2009.2014894
intvolume: '        17'
issue: '5'
keyword:
- AURORA2 databases
- AURORA4 databases
- automatic speech recognition
- feedback structures
- hidden Markov models
- HMM
- iterative methods
- iterative speech feature enhancement
- model probabilities
- speech decoding
- speech enhancement
- speech feature distribution
- speech recognition
- switching linear dynamic models
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-1.pdf
oa: '1'
page: 974-984
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Approaches to Iterative Speech Feature Enhancement and Recognition
type: journal_article
user_id: '44006'
volume: 17
year: '2009'
...
---
_id: '11935'
abstract:
- lang: eng
  text: The generalized sidelobe canceller by Griffith and Jim is a robust beamforming
    method to enhance a desired (speech) signal in the presence of stationary noise.
    Its performance depends to a high degree on the construction of the blocking matrix
    which produces noise reference signals for the subsequent adaptive interference
    canceller. Especially in reverberated environments the beamformer may suffer from
    signal leakage and reduced noise suppression. In this paper a new blocking matrix
    is proposed. It is based on a generalized eigenvalue problem whose solution provides
    an indirect estimation of the transfer functions from the source to the sensors.
    The quality of the new generalized eigenvector blocking matrix is studied in simulated
    rooms with different reverberation times and is compared to alternatives proposed
    in the literature.
author:
- first_name: Ernst
  full_name: Warsitz, Ernst
  last_name: Warsitz
- first_name: Alexander
  full_name: Krueger, Alexander
  last_name: Krueger
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Warsitz E, Krueger A, Haeb-Umbach R. Speech enhancement with a new generalized
    eigenvector blocking matrix for application in a generalized sidelobe canceller.
    In: <i>IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2008)</i>. ; 2008:73-76. doi:<a href="https://doi.org/10.1109/ICASSP.2008.4517549">10.1109/ICASSP.2008.4517549</a>'
  apa: Warsitz, E., Krueger, A., &#38; Haeb-Umbach, R. (2008). Speech enhancement
    with a new generalized eigenvector blocking matrix for application in a generalized
    sidelobe canceller. In <i>IEEE International Conference on Acoustics, Speech and
    Signal Processing (ICASSP 2008)</i> (pp. 73–76). <a href="https://doi.org/10.1109/ICASSP.2008.4517549">https://doi.org/10.1109/ICASSP.2008.4517549</a>
  bibtex: '@inproceedings{Warsitz_Krueger_Haeb-Umbach_2008, title={Speech enhancement
    with a new generalized eigenvector blocking matrix for application in a generalized
    sidelobe canceller}, DOI={<a href="https://doi.org/10.1109/ICASSP.2008.4517549">10.1109/ICASSP.2008.4517549</a>},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2008)}, author={Warsitz, Ernst and Krueger, Alexander and Haeb-Umbach,
    Reinhold}, year={2008}, pages={73–76} }'
  chicago: Warsitz, Ernst, Alexander Krueger, and Reinhold Haeb-Umbach. “Speech Enhancement
    with a New Generalized Eigenvector Blocking Matrix for Application in a Generalized
    Sidelobe Canceller.” In <i>IEEE International Conference on Acoustics, Speech
    and Signal Processing (ICASSP 2008)</i>, 73–76, 2008. <a href="https://doi.org/10.1109/ICASSP.2008.4517549">https://doi.org/10.1109/ICASSP.2008.4517549</a>.
  ieee: E. Warsitz, A. Krueger, and R. Haeb-Umbach, “Speech enhancement with a new
    generalized eigenvector blocking matrix for application in a generalized sidelobe
    canceller,” in <i>IEEE International Conference on Acoustics, Speech and Signal
    Processing (ICASSP 2008)</i>, 2008, pp. 73–76.
  mla: Warsitz, Ernst, et al. “Speech Enhancement with a New Generalized Eigenvector
    Blocking Matrix for Application in a Generalized Sidelobe Canceller.” <i>IEEE
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>,
    2008, pp. 73–76, doi:<a href="https://doi.org/10.1109/ICASSP.2008.4517549">10.1109/ICASSP.2008.4517549</a>.
  short: 'E. Warsitz, A. Krueger, R. Haeb-Umbach, in: IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 73–76.'
date_created: 2019-07-12T05:31:06Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2008.4517549
keyword:
- adaptive interference canceller
- adaptive signal processing
- array signal processing
- beamforming method
- eigenvalues and eigenfunctions
- generalized eigenvector blocking matrix
- generalized sidelobe canceller
- interference suppression
- matrix algebra
- noise suppression
- speech enhancement
- transfer function estimation
- transfer functions
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2008/WaKrHa08.pdf
oa: '1'
page: 73-76
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2008)
status: public
title: Speech enhancement with a new generalized eigenvector blocking matrix for application
  in a generalized sidelobe canceller
type: conference
user_id: '44006'
year: '2008'
...
---
_id: '11939'
abstract:
- lang: eng
  text: In this paper a switching linear dynamical model (SLDM) approach for speech
    feature enhancement is improved by employing more accurate models for the dynamics
    of speech and noise. The model of the clean speech feature trajectory is improved
    by augmenting the state vector to capture information derived from the delta features.
    Further a hidden noise state variable is introduced to obtain a more elaborated
    model for the noise dynamics. Approximate Bayesian inference in the SLDM is carried
    out by a bank of extended Kalman filters, whose outputs are combined according
    to the a posteriori probability of the individual state models. Experimental results
    on the AURORA2 database show improved recognition accuracy.
author:
- first_name: Stefan
  full_name: Windmann, Stefan
  last_name: Windmann
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Windmann S, Haeb-Umbach R. Modeling the dynamics of speech and noise for speech
    feature enhancement in ASR. In: <i>IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2008)</i>. ; 2008:4409-4412. doi:<a href="https://doi.org/10.1109/ICASSP.2008.4518633">10.1109/ICASSP.2008.4518633</a>'
  apa: Windmann, S., &#38; Haeb-Umbach, R. (2008). Modeling the dynamics of speech
    and noise for speech feature enhancement in ASR. In <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2008)</i> (pp. 4409–4412).
    <a href="https://doi.org/10.1109/ICASSP.2008.4518633">https://doi.org/10.1109/ICASSP.2008.4518633</a>
  bibtex: '@inproceedings{Windmann_Haeb-Umbach_2008, title={Modeling the dynamics
    of speech and noise for speech feature enhancement in ASR}, DOI={<a href="https://doi.org/10.1109/ICASSP.2008.4518633">10.1109/ICASSP.2008.4518633</a>},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2008)}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2008},
    pages={4409–4412} }'
  chicago: Windmann, Stefan, and Reinhold Haeb-Umbach. “Modeling the Dynamics of Speech
    and Noise for Speech Feature Enhancement in ASR.” In <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 4409–12, 2008. <a
    href="https://doi.org/10.1109/ICASSP.2008.4518633">https://doi.org/10.1109/ICASSP.2008.4518633</a>.
  ieee: S. Windmann and R. Haeb-Umbach, “Modeling the dynamics of speech and noise
    for speech feature enhancement in ASR,” in <i>IEEE International Conference on
    Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 2008, pp. 4409–4412.
  mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Modeling the Dynamics of Speech
    and Noise for Speech Feature Enhancement in ASR.” <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 2008, pp. 4409–12,
    doi:<a href="https://doi.org/10.1109/ICASSP.2008.4518633">10.1109/ICASSP.2008.4518633</a>.
  short: 'S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2008), 2008, pp. 4409–4412.'
date_created: 2019-07-12T05:31:11Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2008.4518633
keyword:
- a posteriori probability
- AURORA2 database
- Bayesian inference
- Bayes methods
- channel bank filters
- extended Kalman filter banks
- hidden noise state variable
- Kalman filters
- noise dynamics
- speech enhancement
- speech feature enhancement
- speech feature trajectory
- switching linear dynamical model approach
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2008/WiHa08-1.pdf
oa: '1'
page: 4409-4412
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2008)
status: public
title: Modeling the dynamics of speech and noise for speech feature enhancement in
  ASR
type: conference
user_id: '44006'
year: '2008'
...
---
_id: '11943'
abstract:
- lang: eng
  text: A marginalized particle filter is proposed for performing single channel speech
    enhancement with a non-linear dynamic state model. The system consists of a particle
    filter for tracking line spectral pair (LSP) parameters and a Kalman filter per
    particle for speech enhancement. The state model for the LSPs has been learnt
    on clean speech training data. In our approach parameters and speech samples are
    processed at different time scales by assuming the parameters to be constant for
    small blocks of data. Further enhancement is obtained by an iteration which can
    be applied on these small blocks. The experiments show that similar SNR gains
    are obtained as with the Kalman-LM-iterative algorithm. However better values
    of the noise level and the log-spectral distance are achieved
author:
- first_name: Stefan
  full_name: Windmann, Stefan
  last_name: Windmann
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Windmann S, Haeb-Umbach R. Iterative Speech Enhancement using a Non-Linear
    Dynamic State Model of Speech and its Parameters. In: <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>. Vol 1. ; 2006:I.
    doi:<a href="https://doi.org/10.1109/ICASSP.2006.1660058">10.1109/ICASSP.2006.1660058</a>'
  apa: Windmann, S., &#38; Haeb-Umbach, R. (2006). Iterative Speech Enhancement using
    a Non-Linear Dynamic State Model of Speech and its Parameters. In <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i> (Vol.
    1, p. I). <a href="https://doi.org/10.1109/ICASSP.2006.1660058">https://doi.org/10.1109/ICASSP.2006.1660058</a>
  bibtex: '@inproceedings{Windmann_Haeb-Umbach_2006, title={Iterative Speech Enhancement
    using a Non-Linear Dynamic State Model of Speech and its Parameters}, volume={1},
    DOI={<a href="https://doi.org/10.1109/ICASSP.2006.1660058">10.1109/ICASSP.2006.1660058</a>},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2006)}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2006},
    pages={I} }'
  chicago: Windmann, Stefan, and Reinhold Haeb-Umbach. “Iterative Speech Enhancement
    Using a Non-Linear Dynamic State Model of Speech and Its Parameters.” In <i>IEEE
    International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>,
    1:I, 2006. <a href="https://doi.org/10.1109/ICASSP.2006.1660058">https://doi.org/10.1109/ICASSP.2006.1660058</a>.
  ieee: S. Windmann and R. Haeb-Umbach, “Iterative Speech Enhancement using a Non-Linear
    Dynamic State Model of Speech and its Parameters,” in <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, 2006, vol. 1, p.
    I.
  mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Iterative Speech Enhancement Using
    a Non-Linear Dynamic State Model of Speech and Its Parameters.” <i>IEEE International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, vol.
    1, 2006, p. I, doi:<a href="https://doi.org/10.1109/ICASSP.2006.1660058">10.1109/ICASSP.2006.1660058</a>.
  short: 'S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2006), 2006, p. I.'
date_created: 2019-07-12T05:31:15Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2006.1660058
intvolume: '         1'
keyword:
- clean speech training data
- iterative methods
- iterative speech enhancement
- Kalman filter
- Kalman filters
- Kalman-LM-iterative algorithm
- line spectral pair parameters
- log-spectral distance
- marginalized particle filter
- noise level
- nonlinear dynamic state speech model
- particle filtering (numerical methods)
- single channel speech enhancement
- SNR gains
- speech enhancement
- speech samples
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2006/WiHa06-2.pdf
oa: '1'
page: I
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2006)
status: public
title: Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech
  and its Parameters
type: conference
user_id: '44006'
volume: 1
year: '2006'
...
---
_id: '11931'
abstract:
- lang: eng
  text: The paper is concerned with binaural signal processing for a bimodal human-robot
    interface with hearing and vision. The two microphone signals are processed to
    obtain an enhanced single-channel input signal for the subsequent speech recognizer
    and to localize the acoustic source, an important information for establishing
    a natural human-robot communication. We utilize a robust adaptive algorithm for
    filter-and-sum beamforming (FSB) and extract speaker direction information from
    the resulting FIR filter coefficients. Further, particle filtering is applied
    which conducts a nonlinear Bayesian tracking of speaker movement. Good location
    accuracy can be achieved even in highly reverberant environments. The results
    obtained outperform the conventional generalized cross correlation (GCC) method.
author:
- first_name: Ernst
  full_name: Warsitz, Ernst
  last_name: Warsitz
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Warsitz E, Haeb-Umbach R. Robust speaker direction estimation with particle
    filtering. In: <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>.
    ; 2004:367-370. doi:<a href="https://doi.org/10.1109/MMSP.2004.1436569">10.1109/MMSP.2004.1436569</a>'
  apa: Warsitz, E., &#38; Haeb-Umbach, R. (2004). Robust speaker direction estimation
    with particle filtering. In <i>IEEE Workshop on Multimedia Signal Processing (MMSP
    2004)</i> (pp. 367–370). <a href="https://doi.org/10.1109/MMSP.2004.1436569">https://doi.org/10.1109/MMSP.2004.1436569</a>
  bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2004, title={Robust speaker direction
    estimation with particle filtering}, DOI={<a href="https://doi.org/10.1109/MMSP.2004.1436569">10.1109/MMSP.2004.1436569</a>},
    booktitle={IEEE Workshop on Multimedia Signal Processing (MMSP 2004)}, author={Warsitz,
    Ernst and Haeb-Umbach, Reinhold}, year={2004}, pages={367–370} }'
  chicago: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation
    with Particle Filtering.” In <i>IEEE Workshop on Multimedia Signal Processing
    (MMSP 2004)</i>, 367–70, 2004. <a href="https://doi.org/10.1109/MMSP.2004.1436569">https://doi.org/10.1109/MMSP.2004.1436569</a>.
  ieee: E. Warsitz and R. Haeb-Umbach, “Robust speaker direction estimation with particle
    filtering,” in <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>,
    2004, pp. 367–370.
  mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation
    with Particle Filtering.” <i>IEEE Workshop on Multimedia Signal Processing (MMSP
    2004)</i>, 2004, pp. 367–70, doi:<a href="https://doi.org/10.1109/MMSP.2004.1436569">10.1109/MMSP.2004.1436569</a>.
  short: 'E. Warsitz, R. Haeb-Umbach, in: IEEE Workshop on Multimedia Signal Processing
    (MMSP 2004), 2004, pp. 367–370.'
date_created: 2019-07-12T05:31:01Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/MMSP.2004.1436569
keyword:
- bimodal human-robot interface
- binaural signal processing
- enhanced single-channel input signal
- filter-and-sum beamforming
- filtering theory
- FIR filter coefficient
- generalized cross correlation method
- microphones
- microphone signal
- nonlinear Bayesian tracking
- particle filtering
- robust adaptive algorithm
- robust speaker direction estimation
- signal processing
- speech enhancement
- speech recognition
- speech recognizer
- user interfaces
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2004/WaHa04.pdf
oa: '1'
page: 367-370
publication: IEEE Workshop on Multimedia Signal Processing (MMSP 2004)
status: public
title: Robust speaker direction estimation with particle filtering
type: conference
user_id: '44006'
year: '2004'
...