---
_id: '11917'
abstract:
- lang: eng
  text: In this paper we present a speech presence probability (SPP) estimation algorithmwhich
    exploits both temporal and spectral correlations of speech. To this end, the SPP
    estimation is formulated as the posterior probability estimation of the states
    of a two-dimensional (2D) Hidden Markov Model (HMM). We derive an iterative algorithm
    to decode the 2D-HMM which is based on the turbo principle. The experimental results
    show that indeed the SPP estimates improve from iteration to iteration, and further
    clearly outperform another state-of-the-art SPP estimation algorithm.
author:
- first_name: Dang Hai Tran
  full_name: Vu, Dang Hai Tran
  last_name: Vu
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Vu DHT, Haeb-Umbach R. Using the turbo principle for exploiting temporal and
    spectral correlations in speech presence probability estimation. In: <i>38th International
    Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>. ; 2013:863-867.
    doi:<a href="https://doi.org/10.1109/ICASSP.2013.6637771">10.1109/ICASSP.2013.6637771</a>'
  apa: Vu, D. H. T., &#38; Haeb-Umbach, R. (2013). Using the turbo principle for exploiting
    temporal and spectral correlations in speech presence probability estimation.
    In <i>38th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2013)</i> (pp. 863–867). <a href="https://doi.org/10.1109/ICASSP.2013.6637771">https://doi.org/10.1109/ICASSP.2013.6637771</a>
  bibtex: '@inproceedings{Vu_Haeb-Umbach_2013, title={Using the turbo principle for
    exploiting temporal and spectral correlations in speech presence probability estimation},
    DOI={<a href="https://doi.org/10.1109/ICASSP.2013.6637771">10.1109/ICASSP.2013.6637771</a>},
    booktitle={38th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2013)}, author={Vu, Dang Hai Tran and Haeb-Umbach, Reinhold}, year={2013},
    pages={863–867} }'
  chicago: Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle
    for Exploiting Temporal and Spectral Correlations in Speech Presence Probability
    Estimation.” In <i>38th International Conference on Acoustics, Speech and Signal
    Processing (ICASSP 2013)</i>, 863–67, 2013. <a href="https://doi.org/10.1109/ICASSP.2013.6637771">https://doi.org/10.1109/ICASSP.2013.6637771</a>.
  ieee: D. H. T. Vu and R. Haeb-Umbach, “Using the turbo principle for exploiting
    temporal and spectral correlations in speech presence probability estimation,”
    in <i>38th International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2013)</i>, 2013, pp. 863–867.
  mla: Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle for
    Exploiting Temporal and Spectral Correlations in Speech Presence Probability Estimation.”
    <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP
    2013)</i>, 2013, pp. 863–67, doi:<a href="https://doi.org/10.1109/ICASSP.2013.6637771">10.1109/ICASSP.2013.6637771</a>.
  short: 'D.H.T. Vu, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.'
date_created: 2019-07-12T05:30:45Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6637771
keyword:
- correlation methods
- estimation theory
- hidden Markov models
- iterative methods
- probability
- spectral analysis
- speech processing
- 2D HMM
- SPP estimates
- iterative algorithm
- posterior probability estimation
- spectral correlation
- speech presence probability estimation
- state-of-the-art SPP estimation algorithm
- temporal correlation
- turbo principle
- two-dimensional hidden Markov model
- Correlation
- Decoding
- Estimation
- Iterative decoding
- Noise
- Speech
- Vectors
language:
- iso: eng
page: 863-867
publication: 38th International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2013)
publication_identifier:
  issn:
  - 1520-6149
status: public
title: Using the turbo principle for exploiting temporal and spectral correlations
  in speech presence probability estimation
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11930'
abstract:
- lang: eng
  text: For human-machine interfaces in distant-talking environments multichannel
    signal processing is often employed to obtain an enhanced signal for subsequent
    processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum
    beamformer to adjust the coefficients of FIR filters to changing acoustic room
    impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient
    ascent algorithm are derived from a constrained optimization problem, which iteratively
    estimates the eigenvector corresponding to the largest eigenvalue of the cross
    power spectral density of the microphone signals. The method does not require
    an explicit estimation of the speaker location. The experimental results show
    fast adaptation and excellent robustness of the proposed algorithm.
author:
- first_name: Ernst
  full_name: Warsitz, Ernst
  last_name: Warsitz
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'Warsitz E, Haeb-Umbach R. Acoustic filter-and-sum beamforming by adaptive
    principal component analysis. In: <i>IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2005)</i>. Vol 4. ; 2005:iv/797-iv/800 Vol.
    4. doi:<a href="https://doi.org/10.1109/ICASSP.2005.1416129">10.1109/ICASSP.2005.1416129</a>'
  apa: Warsitz, E., &#38; Haeb-Umbach, R. (2005). Acoustic filter-and-sum beamforming
    by adaptive principal component analysis. In <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2005)</i> (Vol. 4, p. iv/797-iv/800
    Vol. 4). <a href="https://doi.org/10.1109/ICASSP.2005.1416129">https://doi.org/10.1109/ICASSP.2005.1416129</a>
  bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2005, title={Acoustic filter-and-sum
    beamforming by adaptive principal component analysis}, volume={4}, DOI={<a href="https://doi.org/10.1109/ICASSP.2005.1416129">10.1109/ICASSP.2005.1416129</a>},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
    (ICASSP 2005)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2005},
    pages={iv/797-iv/800 Vol. 4} }'
  chicago: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming
    by Adaptive Principal Component Analysis.” In <i>IEEE International Conference
    on Acoustics, Speech and Signal Processing (ICASSP 2005)</i>, 4:iv/797-iv/800
    Vol. 4, 2005. <a href="https://doi.org/10.1109/ICASSP.2005.1416129">https://doi.org/10.1109/ICASSP.2005.1416129</a>.
  ieee: E. Warsitz and R. Haeb-Umbach, “Acoustic filter-and-sum beamforming by adaptive
    principal component analysis,” in <i>IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2005)</i>, 2005, vol. 4, p. iv/797-iv/800
    Vol. 4.
  mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming
    by Adaptive Principal Component Analysis.” <i>IEEE International Conference on
    Acoustics, Speech and Signal Processing (ICASSP 2005)</i>, vol. 4, 2005, p. iv/797-iv/800
    Vol. 4, doi:<a href="https://doi.org/10.1109/ICASSP.2005.1416129">10.1109/ICASSP.2005.1416129</a>.
  short: 'E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
    Speech and Signal Processing (ICASSP 2005), 2005, p. iv/797-iv/800 Vol. 4.'
date_created: 2019-07-12T05:31:00Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2005.1416129
intvolume: '         4'
keyword:
- acoustic filter-and-sum beamforming
- acoustic room impulses
- acoustic signal processing
- adaptive principal component analysis
- adaptive signal processing
- architectural acoustics
- constrained optimization problem
- cross power spectral density
- deterministic algorithm
- deterministic algorithms
- distant-talking environments
- eigenvalues and eigenfunctions
- eigenvector
- enhanced signal
- filter-and-sum beamformer
- FIR filter coefficients
- FIR filter coefficients
- FIR filters
- gradient methods
- human-machine interfaces
- iterative estimation
- iterative methods
- largest eigenvalue
- microphone signals
- multichannel signal processing
- optimisation
- principal component analysis
- spectral analysis
- stochastic gradient ascent algorithm
- stochastic processes
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2005/WaHa05.pdf
oa: '1'
page: iv/797-iv/800 Vol. 4
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
  (ICASSP 2005)
status: public
title: Acoustic filter-and-sum beamforming by adaptive principal component analysis
type: conference
user_id: '44006'
volume: 4
year: '2005'
...