---
_id: '11820'
abstract:
- lang: eng
text: In this paper, we derive an uncertainty decoding rule for automatic speech
recognition (ASR), which accounts for both corrupted observations and inter-frame
correlation. The conditional independence assumption, prevalent in hidden Markov
model-based ASR, is relaxed to obtain a clean speech posterior that is conditioned
on the complete observed feature vector sequence. This is a more informative posterior
than one conditioned only on the current observation. The novel decoding is used
to obtain a transmission-error robust remote ASR system, where the speech capturing
unit is connected to the decoder via an error-prone communication network. We
show how the clean speech posterior can be computed for communication links being
characterized by either bit errors or packet loss. Recognition results are presented
for both distributed and network speech recognition, where in the latter case
common voice-over-IP codecs are employed.
author:
- first_name: Valentin
full_name: Ion, Valentin
last_name: Ion
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Ion V, Haeb-Umbach R. A Novel Uncertainty Decoding Rule With Applications to
Transmission Error Robust Speech Recognition. IEEE Transactions on Audio, Speech,
and Language Processing. 2008;16(5):1047-1060. doi:10.1109/TASL.2008.925879
apa: Ion, V., & Haeb-Umbach, R. (2008). A Novel Uncertainty Decoding Rule With
Applications to Transmission Error Robust Speech Recognition. IEEE Transactions
on Audio, Speech, and Language Processing, 16(5), 1047–1060. https://doi.org/10.1109/TASL.2008.925879
bibtex: '@article{Ion_Haeb-Umbach_2008, title={A Novel Uncertainty Decoding Rule
With Applications to Transmission Error Robust Speech Recognition}, volume={16},
DOI={10.1109/TASL.2008.925879},
number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing},
author={Ion, Valentin and Haeb-Umbach, Reinhold}, year={2008}, pages={1047–1060}
}'
chicago: 'Ion, Valentin, and Reinhold Haeb-Umbach. “A Novel Uncertainty Decoding
Rule With Applications to Transmission Error Robust Speech Recognition.” IEEE
Transactions on Audio, Speech, and Language Processing 16, no. 5 (2008): 1047–60.
https://doi.org/10.1109/TASL.2008.925879.'
ieee: V. Ion and R. Haeb-Umbach, “A Novel Uncertainty Decoding Rule With Applications
to Transmission Error Robust Speech Recognition,” IEEE Transactions on Audio,
Speech, and Language Processing, vol. 16, no. 5, pp. 1047–1060, 2008.
mla: Ion, Valentin, and Reinhold Haeb-Umbach. “A Novel Uncertainty Decoding Rule
With Applications to Transmission Error Robust Speech Recognition.” IEEE Transactions
on Audio, Speech, and Language Processing, vol. 16, no. 5, 2008, pp. 1047–60,
doi:10.1109/TASL.2008.925879.
short: V. Ion, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language
Processing 16 (2008) 1047–1060.
date_created: 2019-07-12T05:28:53Z
date_updated: 2022-01-06T06:51:10Z
department:
- _id: '54'
doi: 10.1109/TASL.2008.925879
intvolume: ' 16'
issue: '5'
keyword:
- automatic speech recognition
- bit errors
- codecs
- communication links
- corrupted observations
- decoding
- distributed speech recognition
- error-prone communication network
- feature vector sequence
- hidden Markov model-based ASR
- hidden Markov models
- inter-frame correlation
- Internet telephony
- network speech recognition
- packet loss
- speech posterior
- speech recognition
- transmission error robust speech recognition
- uncertainty decoding
- voice-over-IP codecs
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2008/IoHa08-1.pdf
oa: '1'
page: 1047-1060
publication: IEEE Transactions on Audio, Speech, and Language Processing
status: public
title: A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust
Speech Recognition
type: journal_article
user_id: '44006'
volume: 16
year: '2008'
...
---
_id: '11824'
abstract:
- lang: eng
text: Soft-feature based speech recognition, which is an example of uncertainty
decoding, has been proven to be a robust error mitigation method for distributed
speech recognition over wireless channels exhibiting bit errors. In this paper
we extend this concept to packet-oriented transmissions. The a posteriori probability
density function of the lost feature vector, given the closest received neighbours,
is computed. In the experiments, the nearest frame repetition, which is shown
to be equivalent to the MAP estimate, outperforms the MMSE estimate for long bursts.
Taking the variance into account at the speech recognition stage results in superior
performance compared to classical schemes using point estimates. A computationally
and memory efficient implementation of the proposed packet loss compensation scheme
based on table lookup is presented
author:
- first_name: Valentin
full_name: Ion, Valentin
last_name: Ion
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ion V, Haeb-Umbach R. An Inexpensive Packet Loss Compensation Scheme for Distributed
Speech Recognition Based on Soft-Features. In: IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2006). Vol 1. ; 2006:I.
doi:10.1109/ICASSP.2006.1659984'
apa: Ion, V., & Haeb-Umbach, R. (2006). An Inexpensive Packet Loss Compensation
Scheme for Distributed Speech Recognition Based on Soft-Features. In IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) (Vol.
1, p. I). https://doi.org/10.1109/ICASSP.2006.1659984
bibtex: '@inproceedings{Ion_Haeb-Umbach_2006, title={An Inexpensive Packet Loss
Compensation Scheme for Distributed Speech Recognition Based on Soft-Features},
volume={1}, DOI={10.1109/ICASSP.2006.1659984},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2006)}, author={Ion, Valentin and Haeb-Umbach, Reinhold}, year={2006},
pages={I} }'
chicago: Ion, Valentin, and Reinhold Haeb-Umbach. “An Inexpensive Packet Loss Compensation
Scheme for Distributed Speech Recognition Based on Soft-Features.” In IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006),
1:I, 2006. https://doi.org/10.1109/ICASSP.2006.1659984.
ieee: V. Ion and R. Haeb-Umbach, “An Inexpensive Packet Loss Compensation Scheme
for Distributed Speech Recognition Based on Soft-Features,” in IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), 2006,
vol. 1, p. I.
mla: Ion, Valentin, and Reinhold Haeb-Umbach. “An Inexpensive Packet Loss Compensation
Scheme for Distributed Speech Recognition Based on Soft-Features.” IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), vol.
1, 2006, p. I, doi:10.1109/ICASSP.2006.1659984.
short: 'V. Ion, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2006), 2006, p. I.'
date_created: 2019-07-12T05:28:58Z
date_updated: 2022-01-06T06:51:10Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2006.1659984
intvolume: ' 1'
keyword:
- distributed speech recognition
- least mean squares methods
- MAP estimate
- maximum likelihood estimation
- MMSE estimate
- packet loss compensation scheme
- packet switched communication
- posteriori probability density function
- robust error mitigation method
- soft-features
- speech recognition
- table lookup
- voice communication
- wireless channels
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2006/IoHa06-2.pdf
oa: '1'
page: I
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2006)
status: public
title: An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition
Based on Soft-Features
type: conference
user_id: '44006'
volume: 1
year: '2006'
...