---
_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'
...