---
_id: '11938'
abstract:
- lang: eng
  text: In this paper, parameter estimation of a state-space model of noise or noisy
    speech cepstra is investigated. A blockwise EM algorithm is derived for the estimation
    of the state and observation noise covariance from noise-only input data. It is
    supposed to be used during the offline training mode of a speech recognizer. Further
    a sequential online EM algorithm is developed to adapt the observation noise covariance
    on noisy speech cepstra at its input. The estimated parameters are then used in
    model-based speech feature enhancement for noise-robust automatic speech recognition.
    Experiments on the AURORA4 database lead to improved recognition results with
    a linear state model compared to the assumption of stationary noise.
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. Parameter Estimation of a State-Space Model of Noise
    for Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language
    Processing</i>. 2009;17(8):1577-1590. doi:<a href="https://doi.org/10.1109/TASL.2009.2023172">10.1109/TASL.2009.2023172</a>
  apa: Windmann, S., &#38; Haeb-Umbach, R. (2009). Parameter Estimation of a State-Space
    Model of Noise for Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech,
    and Language Processing</i>, <i>17</i>(8), 1577–1590. <a href="https://doi.org/10.1109/TASL.2009.2023172">https://doi.org/10.1109/TASL.2009.2023172</a>
  bibtex: '@article{Windmann_Haeb-Umbach_2009, title={Parameter Estimation of a State-Space
    Model of Noise for Robust Speech Recognition}, volume={17}, DOI={<a href="https://doi.org/10.1109/TASL.2009.2023172">10.1109/TASL.2009.2023172</a>},
    number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
    author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={1577–1590}
    }'
  chicago: 'Windmann, Stefan, and Reinhold Haeb-Umbach. “Parameter Estimation of a
    State-Space Model of Noise for Robust Speech Recognition.” <i>IEEE Transactions
    on Audio, Speech, and Language Processing</i> 17, no. 8 (2009): 1577–90. <a href="https://doi.org/10.1109/TASL.2009.2023172">https://doi.org/10.1109/TASL.2009.2023172</a>.'
  ieee: S. Windmann and R. Haeb-Umbach, “Parameter Estimation of a State-Space Model
    of Noise for Robust Speech Recognition,” <i>IEEE Transactions on Audio, Speech,
    and Language Processing</i>, vol. 17, no. 8, pp. 1577–1590, 2009.
  mla: Windmann, Stefan, and Reinhold Haeb-Umbach. “Parameter Estimation of a State-Space
    Model of Noise for Robust Speech Recognition.” <i>IEEE Transactions on Audio,
    Speech, and Language Processing</i>, vol. 17, no. 8, 2009, pp. 1577–90, doi:<a
    href="https://doi.org/10.1109/TASL.2009.2023172">10.1109/TASL.2009.2023172</a>.
  short: S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
    Processing 17 (2009) 1577–1590.
date_created: 2019-07-12T05:31:09Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/TASL.2009.2023172
intvolume: '        17'
issue: '8'
keyword:
- AURORA4 database
- blockwise EM algorithm
- covariance analysis
- linear state model
- noise covariance
- noise-robust automatic speech recognition
- noisy speech cepstra
- offline training mode
- parameter estimation
- speech recognition
- speech recognition equipment
- speech recognizer
- state-space methods
- state-space model
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-2.pdf
oa: '1'
page: 1577-1590
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition
type: journal_article
user_id: '44006'
volume: 17
year: '2009'
...