---
_id: '33816'
author:
- first_name: Tobias
full_name: Gburrek, Tobias
id: '44006'
last_name: Gburrek
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Tobias
full_name: Cord-Landwehr, Tobias
id: '44393'
last_name: Cord-Landwehr
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Gburrek T, Boeddeker C, von Neumann T, Cord-Landwehr T, Schmalenstroeer J,
Haeb-Umbach R. A Meeting Transcription System for an Ad-Hoc Acoustic Sensor
Network. arXiv; 2022. doi:10.48550/ARXIV.2205.00944
apa: Gburrek, T., Boeddeker, C., von Neumann, T., Cord-Landwehr, T., Schmalenstroeer,
J., & Haeb-Umbach, R. (2022). A Meeting Transcription System for an Ad-Hoc
Acoustic Sensor Network. arXiv. https://doi.org/10.48550/ARXIV.2205.00944
bibtex: '@book{Gburrek_Boeddeker_von Neumann_Cord-Landwehr_Schmalenstroeer_Haeb-Umbach_2022,
title={A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network},
DOI={10.48550/ARXIV.2205.00944},
publisher={arXiv}, author={Gburrek, Tobias and Boeddeker, Christoph and von Neumann,
Thilo and Cord-Landwehr, Tobias and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold},
year={2022} }'
chicago: Gburrek, Tobias, Christoph Boeddeker, Thilo von Neumann, Tobias Cord-Landwehr,
Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. A Meeting Transcription System
for an Ad-Hoc Acoustic Sensor Network. arXiv, 2022. https://doi.org/10.48550/ARXIV.2205.00944.
ieee: T. Gburrek, C. Boeddeker, T. von Neumann, T. Cord-Landwehr, J. Schmalenstroeer,
and R. Haeb-Umbach, A Meeting Transcription System for an Ad-Hoc Acoustic Sensor
Network. arXiv, 2022.
mla: Gburrek, Tobias, et al. A Meeting Transcription System for an Ad-Hoc Acoustic
Sensor Network. arXiv, 2022, doi:10.48550/ARXIV.2205.00944.
short: T. Gburrek, C. Boeddeker, T. von Neumann, T. Cord-Landwehr, J. Schmalenstroeer,
R. Haeb-Umbach, A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network,
arXiv, 2022.
date_created: 2022-10-18T11:10:58Z
date_updated: 2025-02-12T09:03:42Z
ddc:
- '004'
department:
- _id: '54'
doi: 10.48550/ARXIV.2205.00944
file:
- access_level: open_access
content_type: application/pdf
creator: tgburrek
date_created: 2023-11-17T06:42:04Z
date_updated: 2023-11-17T06:42:04Z
file_id: '48992'
file_name: meeting_transcription_22.pdf
file_size: 199006
relation: main_file
file_date_updated: 2023-11-17T06:42:04Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
- _id: '508'
grant_number: '448568305'
name: Automatische Transkription von Gesprächssituationen
publisher: arXiv
status: public
title: A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network
type: misc
user_id: '40767'
year: '2022'
...
---
_id: '33954'
author:
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Tobias
full_name: Cord-Landwehr, Tobias
id: '44393'
last_name: Cord-Landwehr
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Boeddeker C, Cord-Landwehr T, von Neumann T, Haeb-Umbach R. An Initialization
Scheme for Meeting Separation with Spatial Mixture Models. In: Interspeech
2022. ISCA; 2022. doi:10.21437/interspeech.2022-10929'
apa: Boeddeker, C., Cord-Landwehr, T., von Neumann, T., & Haeb-Umbach, R. (2022).
An Initialization Scheme for Meeting Separation with Spatial Mixture Models. Interspeech
2022. https://doi.org/10.21437/interspeech.2022-10929
bibtex: '@inproceedings{Boeddeker_Cord-Landwehr_von Neumann_Haeb-Umbach_2022, title={An
Initialization Scheme for Meeting Separation with Spatial Mixture Models}, DOI={10.21437/interspeech.2022-10929},
booktitle={Interspeech 2022}, publisher={ISCA}, author={Boeddeker, Christoph and
Cord-Landwehr, Tobias and von Neumann, Thilo and Haeb-Umbach, Reinhold}, year={2022}
}'
chicago: Boeddeker, Christoph, Tobias Cord-Landwehr, Thilo von Neumann, and Reinhold
Haeb-Umbach. “An Initialization Scheme for Meeting Separation with Spatial Mixture
Models.” In Interspeech 2022. ISCA, 2022. https://doi.org/10.21437/interspeech.2022-10929.
ieee: 'C. Boeddeker, T. Cord-Landwehr, T. von Neumann, and R. Haeb-Umbach, “An Initialization
Scheme for Meeting Separation with Spatial Mixture Models,” 2022, doi: 10.21437/interspeech.2022-10929.'
mla: Boeddeker, Christoph, et al. “An Initialization Scheme for Meeting Separation
with Spatial Mixture Models.” Interspeech 2022, ISCA, 2022, doi:10.21437/interspeech.2022-10929.
short: 'C. Boeddeker, T. Cord-Landwehr, T. von Neumann, R. Haeb-Umbach, in: Interspeech
2022, ISCA, 2022.'
date_created: 2022-10-28T10:53:56Z
date_updated: 2025-02-12T09:06:56Z
department:
- _id: '54'
doi: 10.21437/interspeech.2022-10929
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.isca-archive.org/interspeech_2022/boeddeker22_interspeech.pdf
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
- _id: '508'
grant_number: '448568305'
name: Automatische Transkription von Gesprächssituationen
publication: Interspeech 2022
publication_status: published
publisher: ISCA
status: public
title: An Initialization Scheme for Meeting Separation with Spatial Mixture Models
type: conference
user_id: '40767'
year: '2022'
...
---
_id: '33958'
abstract:
- lang: eng
text: Recent speaker diarization studies showed that integration of end-to-end neural
diarization (EEND) and clustering-based diarization is a promising approach for
achieving state-of-the-art performance on various tasks. Such an approach first
divides an observed signal into fixed-length segments, then performs {\it segment-level}
local diarization based on an EEND module, and merges the segment-level results
via clustering to form a final global diarization result. The segmentation is
done to limit the number of speakers in each segment since the current EEND cannot
handle a large number of speakers. In this paper, we argue that such an approach
involving the segmentation has several issues; for example, it inevitably faces
a dilemma that larger segment sizes increase both the context available for enhancing
the performance and the number of speakers for the local EEND module to handle.
To resolve such a problem, this paper proposes a novel framework that performs
diarization without segmentation. However, it can still handle challenging data
containing many speakers and a significant amount of overlapping speech. The proposed
method can take an entire meeting for inference and perform {\it utterance-by-utterance}
diarization that clusters utterance activities in terms of speakers. To this end,
we leverage a neural network training scheme called Graph-PIT proposed recently
for neural source separation. Experiments with simulated active-meeting-like data
and CALLHOME data show the superiority of the proposed approach over the conventional
methods.
author:
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Kinoshita K, von Neumann T, Delcroix M, Boeddeker C, Haeb-Umbach R. Utterance-by-utterance
overlap-aware neural diarization with Graph-PIT. In: Proc. Interspeech 2022.
ISCA; 2022:1486-1490. doi:10.21437/Interspeech.2022-11408'
apa: Kinoshita, K., von Neumann, T., Delcroix, M., Boeddeker, C., & Haeb-Umbach,
R. (2022). Utterance-by-utterance overlap-aware neural diarization with Graph-PIT.
Proc. Interspeech 2022, 1486–1490. https://doi.org/10.21437/Interspeech.2022-11408
bibtex: '@inproceedings{Kinoshita_von Neumann_Delcroix_Boeddeker_Haeb-Umbach_2022,
title={Utterance-by-utterance overlap-aware neural diarization with Graph-PIT},
DOI={10.21437/Interspeech.2022-11408},
booktitle={Proc. Interspeech 2022}, publisher={ISCA}, author={Kinoshita, Keisuke
and von Neumann, Thilo and Delcroix, Marc and Boeddeker, Christoph and Haeb-Umbach,
Reinhold}, year={2022}, pages={1486–1490} }'
chicago: Kinoshita, Keisuke, Thilo von Neumann, Marc Delcroix, Christoph Boeddeker,
and Reinhold Haeb-Umbach. “Utterance-by-Utterance Overlap-Aware Neural Diarization
with Graph-PIT.” In Proc. Interspeech 2022, 1486–90. ISCA, 2022. https://doi.org/10.21437/Interspeech.2022-11408.
ieee: 'K. Kinoshita, T. von Neumann, M. Delcroix, C. Boeddeker, and R. Haeb-Umbach,
“Utterance-by-utterance overlap-aware neural diarization with Graph-PIT,” in Proc.
Interspeech 2022, 2022, pp. 1486–1490, doi: 10.21437/Interspeech.2022-11408.'
mla: Kinoshita, Keisuke, et al. “Utterance-by-Utterance Overlap-Aware Neural Diarization
with Graph-PIT.” Proc. Interspeech 2022, ISCA, 2022, pp. 1486–90, doi:10.21437/Interspeech.2022-11408.
short: 'K. Kinoshita, T. von Neumann, M. Delcroix, C. Boeddeker, R. Haeb-Umbach,
in: Proc. Interspeech 2022, ISCA, 2022, pp. 1486–1490.'
conference:
name: Interspeech 2022
date_created: 2022-10-28T12:07:57Z
date_updated: 2025-02-12T09:09:05Z
department:
- _id: '54'
doi: 10.21437/Interspeech.2022-11408
language:
- iso: eng
main_file_link:
- url: https://www.isca-archive.org/interspeech_2022/kinoshita22_interspeech.pdf
page: 1486-1490
publication: Proc. Interspeech 2022
publication_status: published
publisher: ISCA
quality_controlled: '1'
status: public
title: Utterance-by-utterance overlap-aware neural diarization with Graph-PIT
type: conference
user_id: '40767'
year: '2022'
...
---
_id: '21065'
abstract:
- lang: eng
text: The machine recognition of speech spoken at a distance from the microphones,
known as far-field automatic speech recognition (ASR), has received a significant
increase of attention in science and industry, which caused or was caused by an
equally significant improvement in recognition accuracy. Meanwhile it has entered
the consumer market with digital home assistants with a spoken language interface
being its most prominent application. Speech recorded at a distance is affected
by various acoustic distortions and, consequently, quite different processing
pipelines have emerged compared to ASR for close-talk speech. A signal enhancement
front-end for dereverberation, source separation and acoustic beamforming is employed
to clean up the speech, and the back-end ASR engine is robustified by multi-condition
training and adaptation. We will also describe the so-called end-to-end approach
to ASR, which is a new promising architecture that has recently been extended
to the far-field scenario. This tutorial article gives an account of the algorithms
used to enable accurate speech recognition from a distance, and it will be seen
that, although deep learning has a significant share in the technological breakthroughs,
a clever combination with traditional signal processing can lead to surprisingly
effective solutions.
author:
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
- first_name: Jahn
full_name: Heymann, Jahn
last_name: Heymann
- first_name: Lukas
full_name: Drude, Lukas
last_name: Drude
- first_name: Shinji
full_name: Watanabe, Shinji
last_name: Watanabe
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Tomohiro
full_name: Nakatani, Tomohiro
last_name: Nakatani
citation:
ama: Haeb-Umbach R, Heymann J, Drude L, Watanabe S, Delcroix M, Nakatani T. Far-Field
Automatic Speech Recognition. Proceedings of the IEEE. 2021;109(2):124-148.
doi:10.1109/JPROC.2020.3018668
apa: Haeb-Umbach, R., Heymann, J., Drude, L., Watanabe, S., Delcroix, M., &
Nakatani, T. (2021). Far-Field Automatic Speech Recognition. Proceedings of
the IEEE, 109(2), 124–148. https://doi.org/10.1109/JPROC.2020.3018668
bibtex: '@article{Haeb-Umbach_Heymann_Drude_Watanabe_Delcroix_Nakatani_2021, title={Far-Field
Automatic Speech Recognition}, volume={109}, DOI={10.1109/JPROC.2020.3018668},
number={2}, journal={Proceedings of the IEEE}, author={Haeb-Umbach, Reinhold and
Heymann, Jahn and Drude, Lukas and Watanabe, Shinji and Delcroix, Marc and Nakatani,
Tomohiro}, year={2021}, pages={124–148} }'
chicago: 'Haeb-Umbach, Reinhold, Jahn Heymann, Lukas Drude, Shinji Watanabe, Marc
Delcroix, and Tomohiro Nakatani. “Far-Field Automatic Speech Recognition.” Proceedings
of the IEEE 109, no. 2 (2021): 124–48. https://doi.org/10.1109/JPROC.2020.3018668.'
ieee: R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, and T. Nakatani,
“Far-Field Automatic Speech Recognition,” Proceedings of the IEEE, vol.
109, no. 2, pp. 124–148, 2021.
mla: Haeb-Umbach, Reinhold, et al. “Far-Field Automatic Speech Recognition.” Proceedings
of the IEEE, vol. 109, no. 2, 2021, pp. 124–48, doi:10.1109/JPROC.2020.3018668.
short: R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, T. Nakatani,
Proceedings of the IEEE 109 (2021) 124–148.
date_created: 2021-01-25T08:15:27Z
date_updated: 2022-01-06T06:54:44Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.1109/JPROC.2020.3018668
file:
- access_level: open_access
content_type: application/pdf
creator: huesera
date_created: 2021-01-25T08:17:23Z
date_updated: 2021-01-25T08:17:23Z
file_id: '21066'
file_name: proceedings_2021_haebumbach_Paper.pdf
file_size: 4173988
relation: main_file
file_date_updated: 2021-01-25T08:17:23Z
has_accepted_license: '1'
intvolume: ' 109'
issue: '2'
language:
- iso: eng
oa: '1'
page: 124-148
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proceedings of the IEEE
status: public
title: Far-Field Automatic Speech Recognition
type: journal_article
user_id: '59789'
volume: 109
year: '2021'
...
---
_id: '28256'
author:
- first_name: Wangyou
full_name: Zhang, Wangyou
last_name: Zhang
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Shinji
full_name: Watanabe, Shinji
last_name: Watanabe
- first_name: Tomohiro
full_name: Nakatani, Tomohiro
last_name: Nakatani
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Tsubasa
full_name: Ochiai, Tsubasa
last_name: Ochiai
- first_name: Naoyuki
full_name: Kamo, Naoyuki
last_name: Kamo
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
- first_name: Yanmin
full_name: Qian, Yanmin
last_name: Qian
citation:
ama: 'Zhang W, Boeddeker C, Watanabe S, et al. End-to-End Dereverberation, Beamforming,
and Speech Recognition with Improved Numerical Stability and Advanced Frontend.
In: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and
Signal Processing (ICASSP). ; 2021. doi:10.1109/icassp39728.2021.9414464'
apa: Zhang, W., Boeddeker, C., Watanabe, S., Nakatani, T., Delcroix, M., Kinoshita,
K., Ochiai, T., Kamo, N., Haeb-Umbach, R., & Qian, Y. (2021). End-to-End Dereverberation,
Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced
Frontend. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP). https://doi.org/10.1109/icassp39728.2021.9414464
bibtex: '@inproceedings{Zhang_Boeddeker_Watanabe_Nakatani_Delcroix_Kinoshita_Ochiai_Kamo_Haeb-Umbach_Qian_2021,
title={End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved
Numerical Stability and Advanced Frontend}, DOI={10.1109/icassp39728.2021.9414464},
booktitle={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)}, author={Zhang, Wangyou and Boeddeker, Christoph
and Watanabe, Shinji and Nakatani, Tomohiro and Delcroix, Marc and Kinoshita,
Keisuke and Ochiai, Tsubasa and Kamo, Naoyuki and Haeb-Umbach, Reinhold and Qian,
Yanmin}, year={2021} }'
chicago: Zhang, Wangyou, Christoph Boeddeker, Shinji Watanabe, Tomohiro Nakatani,
Marc Delcroix, Keisuke Kinoshita, Tsubasa Ochiai, Naoyuki Kamo, Reinhold Haeb-Umbach,
and Yanmin Qian. “End-to-End Dereverberation, Beamforming, and Speech Recognition
with Improved Numerical Stability and Advanced Frontend.” In ICASSP 2021 -
2021 IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP), 2021. https://doi.org/10.1109/icassp39728.2021.9414464.
ieee: 'W. Zhang et al., “End-to-End Dereverberation, Beamforming, and Speech
Recognition with Improved Numerical Stability and Advanced Frontend,” 2021, doi:
10.1109/icassp39728.2021.9414464.'
mla: Zhang, Wangyou, et al. “End-to-End Dereverberation, Beamforming, and Speech
Recognition with Improved Numerical Stability and Advanced Frontend.” ICASSP
2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP), 2021, doi:10.1109/icassp39728.2021.9414464.
short: 'W. Zhang, C. Boeddeker, S. Watanabe, T. Nakatani, M. Delcroix, K. Kinoshita,
T. Ochiai, N. Kamo, R. Haeb-Umbach, Y. Qian, in: ICASSP 2021 - 2021 IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.'
date_created: 2021-12-03T11:31:42Z
date_updated: 2022-01-13T08:31:27Z
department:
- _id: '54'
doi: 10.1109/icassp39728.2021.9414464
language:
- iso: eng
publication: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)
publication_status: published
status: public
title: End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved
Numerical Stability and Advanced Frontend
type: conference
user_id: '40767'
year: '2021'
...
---
_id: '24000'
author:
- first_name: Jens
full_name: Heitkaemper, Jens
id: '27643'
last_name: Heitkaemper
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- 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: 'Heitkaemper J, Schmalenstroeer J, Ion V, Haeb-Umbach R. A Database for Research
on Detection and Enhancement of Speech Transmitted over HF links. In: Speech
Communication; 14th ITG-Symposium. ; 2021:1-5.'
apa: Heitkaemper, J., Schmalenstroeer, J., Ion, V., & Haeb-Umbach, R. (2021).
A Database for Research on Detection and Enhancement of Speech Transmitted over
HF links. Speech Communication; 14th ITG-Symposium, 1–5.
bibtex: '@inproceedings{Heitkaemper_Schmalenstroeer_Ion_Haeb-Umbach_2021, title={A
Database for Research on Detection and Enhancement of Speech Transmitted over
HF links}, booktitle={Speech Communication; 14th ITG-Symposium}, author={Heitkaemper,
Jens and Schmalenstroeer, Joerg and Ion, Valentin and Haeb-Umbach, Reinhold},
year={2021}, pages={1–5} }'
chicago: Heitkaemper, Jens, Joerg Schmalenstroeer, Valentin Ion, and Reinhold Haeb-Umbach.
“A Database for Research on Detection and Enhancement of Speech Transmitted over
HF Links.” In Speech Communication; 14th ITG-Symposium, 1–5, 2021.
ieee: J. Heitkaemper, J. Schmalenstroeer, V. Ion, and R. Haeb-Umbach, “A Database
for Research on Detection and Enhancement of Speech Transmitted over HF links,”
in Speech Communication; 14th ITG-Symposium, 2021, pp. 1–5.
mla: Heitkaemper, Jens, et al. “A Database for Research on Detection and Enhancement
of Speech Transmitted over HF Links.” Speech Communication; 14th ITG-Symposium,
2021, pp. 1–5.
short: 'J. Heitkaemper, J. Schmalenstroeer, V. Ion, R. Haeb-Umbach, in: Speech Communication;
14th ITG-Symposium, 2021, pp. 1–5.'
date_created: 2021-09-09T08:41:25Z
date_updated: 2023-10-26T08:06:57Z
department:
- _id: '54'
language:
- iso: eng
page: 1-5
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Speech Communication; 14th ITG-Symposium
quality_controlled: '1'
status: public
title: A Database for Research on Detection and Enhancement of Speech Transmitted
over HF links
type: conference
user_id: '460'
year: '2021'
...
---
_id: '44843'
abstract:
- lang: eng
text: "Unsupervised blind source separation methods do not require a training phase\r\nand
thus cannot suffer from a train-test mismatch, which is a common concern in\r\nneural
network based source separation. The unsupervised techniques can be\r\ncategorized
in two classes, those building upon the sparsity of speech in the\r\nShort-Time
Fourier transform domain and those exploiting non-Gaussianity or\r\nnon-stationarity
of the source signals. In this contribution, spatial mixture\r\nmodels which fall
in the first category and independent vector analysis (IVA)\r\nas a representative
of the second category are compared w.r.t. their separation\r\nperformance and
the performance of a downstream speech recognizer on a\r\nreverberant dataset
of reasonable size. Furthermore, we introduce a serial\r\nconcatenation of the
two, where the result of the mixture model serves as\r\ninitialization of IVA,
which achieves significantly better WER performance than\r\neach algorithm individually
and even approaches the performance of a much more\r\ncomplex neural network based
technique."
author:
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Frederik
full_name: Rautenberg, Frederik
id: '72602'
last_name: Rautenberg
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Boeddeker C, Rautenberg F, Haeb-Umbach R. A Comparison and Combination of
Unsupervised Blind Source Separation Techniques. In: ITG Conference on Speech
Communication. ; 2021.'
apa: Boeddeker, C., Rautenberg, F., & Haeb-Umbach, R. (2021). A Comparison and
Combination of Unsupervised Blind Source Separation Techniques. ITG Conference
on Speech Communication. ITG Conference on Speech Communication, Kiel.
bibtex: '@inproceedings{Boeddeker_Rautenberg_Haeb-Umbach_2021, title={A Comparison
and Combination of Unsupervised Blind Source Separation Techniques}, booktitle={ITG
Conference on Speech Communication}, author={Boeddeker, Christoph and Rautenberg,
Frederik and Haeb-Umbach, Reinhold}, year={2021} }'
chicago: Boeddeker, Christoph, Frederik Rautenberg, and Reinhold Haeb-Umbach. “A
Comparison and Combination of Unsupervised Blind Source Separation Techniques.”
In ITG Conference on Speech Communication, 2021.
ieee: C. Boeddeker, F. Rautenberg, and R. Haeb-Umbach, “A Comparison and Combination
of Unsupervised Blind Source Separation Techniques,” presented at the ITG Conference
on Speech Communication, Kiel, 2021.
mla: Boeddeker, Christoph, et al. “A Comparison and Combination of Unsupervised
Blind Source Separation Techniques.” ITG Conference on Speech Communication,
2021.
short: 'C. Boeddeker, F. Rautenberg, R. Haeb-Umbach, in: ITG Conference on Speech
Communication, 2021.'
conference:
location: Kiel
name: ITG Conference on Speech Communication
date_created: 2023-05-15T07:59:33Z
date_updated: 2023-11-15T15:29:32Z
ddc:
- '000'
department:
- _id: '54'
external_id:
arxiv:
- '2106.05627'
file:
- access_level: open_access
content_type: application/pdf
creator: frra
date_created: 2023-05-16T08:37:31Z
date_updated: 2023-11-15T15:29:32Z
file_id: '44856'
file_name: 2106.05627.pdf
file_size: 295972
relation: main_file
file_date_updated: 2023-11-15T15:29:32Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/2106.05627.pdf
oa: '1'
publication: ITG Conference on Speech Communication
status: public
title: A Comparison and Combination of Unsupervised Blind Source Separation Techniques
type: conference
user_id: '40767'
year: '2021'
...
---
_id: '28259'
author:
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Wangyou
full_name: Zhang, Wangyou
last_name: Zhang
- first_name: Tomohiro
full_name: Nakatani, Tomohiro
last_name: Nakatani
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Tsubasa
full_name: Ochiai, Tsubasa
last_name: Ochiai
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Naoyuki
full_name: Kamo, Naoyuki
last_name: Kamo
- first_name: Yanmin
full_name: Qian, Yanmin
last_name: Qian
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Boeddeker C, Zhang W, Nakatani T, et al. Convolutive Transfer Function Invariant
SDR Training Criteria for Multi-Channel Reverberant Speech Separation. In: ICASSP
2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP). ; 2021. doi:10.1109/icassp39728.2021.9414661'
apa: Boeddeker, C., Zhang, W., Nakatani, T., Kinoshita, K., Ochiai, T., Delcroix,
M., Kamo, N., Qian, Y., & Haeb-Umbach, R. (2021). Convolutive Transfer Function
Invariant SDR Training Criteria for Multi-Channel Reverberant Speech Separation.
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP). https://doi.org/10.1109/icassp39728.2021.9414661
bibtex: '@inproceedings{Boeddeker_Zhang_Nakatani_Kinoshita_Ochiai_Delcroix_Kamo_Qian_Haeb-Umbach_2021,
title={Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel
Reverberant Speech Separation}, DOI={10.1109/icassp39728.2021.9414661},
booktitle={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)}, author={Boeddeker, Christoph and Zhang, Wangyou
and Nakatani, Tomohiro and Kinoshita, Keisuke and Ochiai, Tsubasa and Delcroix,
Marc and Kamo, Naoyuki and Qian, Yanmin and Haeb-Umbach, Reinhold}, year={2021}
}'
chicago: Boeddeker, Christoph, Wangyou Zhang, Tomohiro Nakatani, Keisuke Kinoshita,
Tsubasa Ochiai, Marc Delcroix, Naoyuki Kamo, Yanmin Qian, and Reinhold Haeb-Umbach.
“Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel
Reverberant Speech Separation.” In ICASSP 2021 - 2021 IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP), 2021. https://doi.org/10.1109/icassp39728.2021.9414661.
ieee: 'C. Boeddeker et al., “Convolutive Transfer Function Invariant SDR
Training Criteria for Multi-Channel Reverberant Speech Separation,” 2021, doi:
10.1109/icassp39728.2021.9414661.'
mla: Boeddeker, Christoph, et al. “Convolutive Transfer Function Invariant SDR Training
Criteria for Multi-Channel Reverberant Speech Separation.” ICASSP 2021 - 2021
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2021, doi:10.1109/icassp39728.2021.9414661.
short: 'C. Boeddeker, W. Zhang, T. Nakatani, K. Kinoshita, T. Ochiai, M. Delcroix,
N. Kamo, Y. Qian, R. Haeb-Umbach, in: ICASSP 2021 - 2021 IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP), 2021.'
date_created: 2021-12-03T12:00:16Z
date_updated: 2023-11-15T15:18:09Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.1109/icassp39728.2021.9414661
file:
- access_level: open_access
content_type: application/pdf
creator: cbj
date_created: 2021-12-03T12:01:20Z
date_updated: 2023-11-15T15:18:08Z
file_id: '28260'
file_name: ICASSP2021_BSSEval.pdf
file_size: 228717
relation: main_file
file_date_updated: 2023-11-15T15:18:08Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)
publication_status: published
status: public
title: Convolutive Transfer Function Invariant SDR Training Criteria for Multi-Channel
Reverberant Speech Separation
type: conference
user_id: '40767'
year: '2021'
...
---
_id: '23998'
author:
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Jens
full_name: Heitkaemper, Jens
id: '27643'
last_name: Heitkaemper
- first_name: Joerg
full_name: Ullmann, Joerg
id: '16256'
last_name: Ullmann
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Schmalenstroeer J, Heitkaemper J, Ullmann J, Haeb-Umbach R. Open Range Pitch
Tracking for Carrier Frequency Difference Estimation from HF Transmitted Speech.
In: 29th European Signal Processing Conference (EUSIPCO). ; 2021:1-5.'
apa: Schmalenstroeer, J., Heitkaemper, J., Ullmann, J., & Haeb-Umbach, R. (2021).
Open Range Pitch Tracking for Carrier Frequency Difference Estimation from HF
Transmitted Speech. 29th European Signal Processing Conference (EUSIPCO),
1–5.
bibtex: '@inproceedings{Schmalenstroeer_Heitkaemper_Ullmann_Haeb-Umbach_2021, title={Open
Range Pitch Tracking for Carrier Frequency Difference Estimation from HF Transmitted
Speech}, booktitle={29th European Signal Processing Conference (EUSIPCO)}, author={Schmalenstroeer,
Joerg and Heitkaemper, Jens and Ullmann, Joerg and Haeb-Umbach, Reinhold}, year={2021},
pages={1–5} }'
chicago: Schmalenstroeer, Joerg, Jens Heitkaemper, Joerg Ullmann, and Reinhold Haeb-Umbach.
“Open Range Pitch Tracking for Carrier Frequency Difference Estimation from HF
Transmitted Speech.” In 29th European Signal Processing Conference (EUSIPCO),
1–5, 2021.
ieee: J. Schmalenstroeer, J. Heitkaemper, J. Ullmann, and R. Haeb-Umbach, “Open
Range Pitch Tracking for Carrier Frequency Difference Estimation from HF Transmitted
Speech,” in 29th European Signal Processing Conference (EUSIPCO), 2021,
pp. 1–5.
mla: Schmalenstroeer, Joerg, et al. “Open Range Pitch Tracking for Carrier Frequency
Difference Estimation from HF Transmitted Speech.” 29th European Signal Processing
Conference (EUSIPCO), 2021, pp. 1–5.
short: 'J. Schmalenstroeer, J. Heitkaemper, J. Ullmann, R. Haeb-Umbach, in: 29th
European Signal Processing Conference (EUSIPCO), 2021, pp. 1–5.'
date_created: 2021-09-09T08:40:04Z
date_updated: 2023-11-15T14:56:38Z
department:
- _id: '54'
extern: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2103.01599
oa: '1'
page: 1-5
publication: 29th European Signal Processing Conference (EUSIPCO)
status: public
title: Open Range Pitch Tracking for Carrier Frequency Difference Estimation from
HF Transmitted Speech
type: conference
user_id: '460'
year: '2021'
...
---
_id: '22528'
abstract:
- lang: eng
text: Due to the ad hoc nature of wireless acoustic sensor networks, the position
of the sensor nodes is typically unknown. This contribution proposes a technique
to estimate the position and orientation of the sensor nodes from the recorded
speech signals. The method assumes that a node comprises a microphone array with
synchronously sampled microphones rather than a single microphone, but does not
require the sampling clocks of the nodes to be synchronized. From the observed
audio signals, the distances between the acoustic sources and arrays, as well
as the directions of arrival, are estimated. They serve as input to a non-linear
least squares problem, from which both the sensor nodes’ positions and orientations,
as well as the source positions, are alternatingly estimated in an iterative process.
Given one set of unknowns, i.e., either the source positions or the sensor nodes’
geometry, the other set of unknowns can be computed in closed-form. The proposed
approach is computationally efficient and the first one, which employs both distance
and directional information for geometry calibration in a common cost function.
Since both distance and direction of arrival measurements suffer from outliers,
e.g., caused by strong reflections of the sound waves on the surfaces of the room,
we introduce measures to deemphasize or remove unreliable measurements. Additionally,
we discuss modifications of our previously proposed deep neural network-based
acoustic distance estimator, to account not only for omnidirectional sources but
also for directional sources. Simulation results show good positioning accuracy
and compare very favorably with alternative approaches from the literature.
author:
- first_name: Tobias
full_name: Gburrek, Tobias
id: '44006'
last_name: Gburrek
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Gburrek T, Schmalenstroeer J, Haeb-Umbach R. Geometry calibration in wireless
acoustic sensor networks utilizing DoA and distance information. EURASIP Journal
on Audio, Speech, and Music Processing. Published online 2021. doi:10.1186/s13636-021-00210-x
apa: Gburrek, T., Schmalenstroeer, J., & Haeb-Umbach, R. (2021). Geometry calibration
in wireless acoustic sensor networks utilizing DoA and distance information. EURASIP
Journal on Audio, Speech, and Music Processing. https://doi.org/10.1186/s13636-021-00210-x
bibtex: '@article{Gburrek_Schmalenstroeer_Haeb-Umbach_2021, title={Geometry calibration
in wireless acoustic sensor networks utilizing DoA and distance information},
DOI={10.1186/s13636-021-00210-x},
journal={EURASIP Journal on Audio, Speech, and Music Processing}, author={Gburrek,
Tobias and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2021} }'
chicago: Gburrek, Tobias, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “Geometry
Calibration in Wireless Acoustic Sensor Networks Utilizing DoA and Distance Information.”
EURASIP Journal on Audio, Speech, and Music Processing, 2021. https://doi.org/10.1186/s13636-021-00210-x.
ieee: 'T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “Geometry calibration
in wireless acoustic sensor networks utilizing DoA and distance information,”
EURASIP Journal on Audio, Speech, and Music Processing, 2021, doi: 10.1186/s13636-021-00210-x.'
mla: Gburrek, Tobias, et al. “Geometry Calibration in Wireless Acoustic Sensor Networks
Utilizing DoA and Distance Information.” EURASIP Journal on Audio, Speech,
and Music Processing, 2021, doi:10.1186/s13636-021-00210-x.
short: T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, EURASIP Journal on Audio,
Speech, and Music Processing (2021).
date_created: 2021-07-05T05:30:15Z
date_updated: 2023-11-17T06:36:17Z
department:
- _id: '54'
doi: 10.1186/s13636-021-00210-x
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://asmp-eurasipjournals.springeropen.com/articles/10.1186/s13636-021-00210-x
oa: '1'
publication: EURASIP Journal on Audio, Speech, and Music Processing
publication_identifier:
issn:
- 1687-4722
publication_status: published
quality_controlled: '1'
status: public
title: Geometry calibration in wireless acoustic sensor networks utilizing DoA and
distance information
type: journal_article
user_id: '44006'
year: '2021'
...
---
_id: '23994'
author:
- first_name: Tobias
full_name: Gburrek, Tobias
id: '44006'
last_name: Gburrek
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Gburrek T, Schmalenstroeer J, Haeb-Umbach R. Iterative Geometry Calibration
from Distance Estimates for Wireless Acoustic Sensor Networks. In: ICASSP 2021
- 2021 IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP). ; 2021. doi:10.1109/icassp39728.2021.9413831'
apa: Gburrek, T., Schmalenstroeer, J., & Haeb-Umbach, R. (2021). Iterative Geometry
Calibration from Distance Estimates for Wireless Acoustic Sensor Networks. ICASSP
2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP). https://doi.org/10.1109/icassp39728.2021.9413831
bibtex: '@inproceedings{Gburrek_Schmalenstroeer_Haeb-Umbach_2021, title={Iterative
Geometry Calibration from Distance Estimates for Wireless Acoustic Sensor Networks},
DOI={10.1109/icassp39728.2021.9413831},
booktitle={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)}, author={Gburrek, Tobias and Schmalenstroeer,
Joerg and Haeb-Umbach, Reinhold}, year={2021} }'
chicago: Gburrek, Tobias, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “Iterative
Geometry Calibration from Distance Estimates for Wireless Acoustic Sensor Networks.”
In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and
Signal Processing (ICASSP), 2021. https://doi.org/10.1109/icassp39728.2021.9413831.
ieee: 'T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “Iterative Geometry Calibration
from Distance Estimates for Wireless Acoustic Sensor Networks,” 2021, doi: 10.1109/icassp39728.2021.9413831.'
mla: Gburrek, Tobias, et al. “Iterative Geometry Calibration from Distance Estimates
for Wireless Acoustic Sensor Networks.” ICASSP 2021 - 2021 IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, doi:10.1109/icassp39728.2021.9413831.
short: 'T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, in: ICASSP 2021 - 2021 IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2021.'
date_created: 2021-09-09T08:30:16Z
date_updated: 2023-11-17T06:30:12Z
ddc:
- '004'
department:
- _id: '54'
doi: 10.1109/icassp39728.2021.9413831
file:
- access_level: open_access
content_type: application/pdf
creator: tgburrek
date_created: 2023-11-17T06:29:40Z
date_updated: 2023-11-17T06:30:11Z
file_id: '48988'
file_name: icassp21.pdf
file_size: 312400
relation: main_file
file_date_updated: 2023-11-17T06:30:11Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
publication: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)
publication_status: published
quality_controlled: '1'
status: public
title: Iterative Geometry Calibration from Distance Estimates for Wireless Acoustic
Sensor Networks
type: conference
user_id: '44006'
year: '2021'
...
---
_id: '23999'
author:
- first_name: Tobias
full_name: Gburrek, Tobias
id: '44006'
last_name: Gburrek
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Gburrek T, Schmalenstroeer J, Haeb-Umbach R. On Source-Microphone Distance
Estimation Using Convolutional Recurrent Neural Networks. In: Speech Communication;
14th ITG-Symposium. ; 2021:1-5.'
apa: Gburrek, T., Schmalenstroeer, J., & Haeb-Umbach, R. (2021). On Source-Microphone
Distance Estimation Using Convolutional Recurrent Neural Networks. Speech Communication;
14th ITG-Symposium, 1–5.
bibtex: '@inproceedings{Gburrek_Schmalenstroeer_Haeb-Umbach_2021, title={On Source-Microphone
Distance Estimation Using Convolutional Recurrent Neural Networks}, booktitle={Speech
Communication; 14th ITG-Symposium}, author={Gburrek, Tobias and Schmalenstroeer,
Joerg and Haeb-Umbach, Reinhold}, year={2021}, pages={1–5} }'
chicago: Gburrek, Tobias, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “On Source-Microphone
Distance Estimation Using Convolutional Recurrent Neural Networks.” In Speech
Communication; 14th ITG-Symposium, 1–5, 2021.
ieee: T. Gburrek, J. Schmalenstroeer, and R. Haeb-Umbach, “On Source-Microphone
Distance Estimation Using Convolutional Recurrent Neural Networks,” in Speech
Communication; 14th ITG-Symposium, 2021, pp. 1–5.
mla: Gburrek, Tobias, et al. “On Source-Microphone Distance Estimation Using Convolutional
Recurrent Neural Networks.” Speech Communication; 14th ITG-Symposium, 2021,
pp. 1–5.
short: 'T. Gburrek, J. Schmalenstroeer, R. Haeb-Umbach, in: Speech Communication;
14th ITG-Symposium, 2021, pp. 1–5.'
date_created: 2021-09-09T08:40:44Z
date_updated: 2023-11-17T06:32:20Z
ddc:
- '004'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: tgburrek
date_created: 2023-11-17T06:31:37Z
date_updated: 2023-11-17T06:31:37Z
file_id: '48989'
file_name: dist_est.pdf
file_size: 449694
relation: main_file
file_date_updated: 2023-11-17T06:31:37Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 1-5
publication: Speech Communication; 14th ITG-Symposium
quality_controlled: '1'
status: public
title: On Source-Microphone Distance Estimation Using Convolutional Recurrent Neural
Networks
type: conference
user_id: '44006'
year: '2021'
...
---
_id: '29304'
abstract:
- lang: eng
text: 'In this work we address disentanglement of style and content in speech signals.
We propose a fully convolutional variational autoencoder employing two encoders:
a content encoder and a style encoder. To foster disentanglement, we propose adversarial
contrastive predictive coding. This new disentanglement method does neither need
parallel data nor any supervision. We show that the proposed technique is capable
of separating speaker and content traits into the two different representations
and show competitive speaker-content disentanglement performance compared to other
unsupervised approaches. We further demonstrate an increased robustness of the
content representation against a train-test mismatch compared to spectral features,
when used for phone recognition.'
author:
- first_name: Janek
full_name: Ebbers, Janek
id: '34851'
last_name: Ebbers
- first_name: Michael
full_name: Kuhlmann, Michael
id: '49871'
last_name: Kuhlmann
- first_name: Tobias
full_name: Cord-Landwehr, Tobias
id: '44393'
last_name: Cord-Landwehr
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ebbers J, Kuhlmann M, Cord-Landwehr T, Haeb-Umbach R. Contrastive Predictive
Coding Supported Factorized Variational Autoencoder for Unsupervised Learning
of Disentangled Speech Representations. In: Proceedings of the IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP). ; 2021:3860–3864.'
apa: Ebbers, J., Kuhlmann, M., Cord-Landwehr, T., & Haeb-Umbach, R. (2021).
Contrastive Predictive Coding Supported Factorized Variational Autoencoder for
Unsupervised Learning of Disentangled Speech Representations. Proceedings of
the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
3860–3864.
bibtex: '@inproceedings{Ebbers_Kuhlmann_Cord-Landwehr_Haeb-Umbach_2021, title={Contrastive
Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised
Learning of Disentangled Speech Representations}, booktitle={Proceedings of the
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
author={Ebbers, Janek and Kuhlmann, Michael and Cord-Landwehr, Tobias and Haeb-Umbach,
Reinhold}, year={2021}, pages={3860–3864} }'
chicago: Ebbers, Janek, Michael Kuhlmann, Tobias Cord-Landwehr, and Reinhold Haeb-Umbach.
“Contrastive Predictive Coding Supported Factorized Variational Autoencoder for
Unsupervised Learning of Disentangled Speech Representations.” In Proceedings
of the IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP), 3860–3864, 2021.
ieee: J. Ebbers, M. Kuhlmann, T. Cord-Landwehr, and R. Haeb-Umbach, “Contrastive
Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised
Learning of Disentangled Speech Representations,” in Proceedings of the IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2021, pp. 3860–3864.
mla: Ebbers, Janek, et al. “Contrastive Predictive Coding Supported Factorized Variational
Autoencoder for Unsupervised Learning of Disentangled Speech Representations.”
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP), 2021, pp. 3860–3864.
short: 'J. Ebbers, M. Kuhlmann, T. Cord-Landwehr, R. Haeb-Umbach, in: Proceedings
of the IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP), 2021, pp. 3860–3864.'
date_created: 2022-01-13T07:55:29Z
date_updated: 2023-11-22T08:29:42Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: ebbers
date_created: 2022-01-13T07:56:30Z
date_updated: 2022-01-13T08:19:19Z
file_id: '29305'
file_name: Template.pdf
file_size: 236628
relation: main_file
file_date_updated: 2022-01-13T08:19:19Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 3860–3864
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP)
quality_controlled: '1'
status: public
title: Contrastive Predictive Coding Supported Factorized Variational Autoencoder
for Unsupervised Learning of Disentangled Speech Representations
type: conference
user_id: '34851'
year: '2021'
...
---
_id: '26770'
abstract:
- lang: eng
text: "Automatic transcription of meetings requires handling of overlapped speech,
which calls for continuous speech separation (CSS) systems. The uPIT criterion
was proposed for utterance-level separation with neural networks and introduces
the constraint that the total number of speakers must not exceed the number of
output channels. When processing meeting-like data in a segment-wise manner, i.e.,
by separating overlapping segments independently and stitching adjacent segments
to continuous output streams, this constraint has to be fulfilled for any segment.
In this contribution, we show that this constraint can be significantly relaxed.
We propose a novel graph-based PIT criterion, which casts the assignment of utterances
to output channels in a graph coloring problem. It only requires that the number
of concurrently active speakers must not exceed the number of output channels.
As a consequence, the system can process an arbitrary number of speakers and arbitrarily
long segments and thus can handle more diverse scenarios.\r\nFurther, the stitching
algorithm for obtaining a consistent output order in neighboring segments is of
less importance and can even be eliminated completely, not the least reducing
the computational effort. Experiments on meeting-style WSJ data show improvements
in recognition performance over using the uPIT criterion. "
author:
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'von Neumann T, Kinoshita K, Boeddeker C, Delcroix M, Haeb-Umbach R. Graph-PIT:
Generalized Permutation Invariant Training for Continuous Separation of Arbitrary
Numbers of Speakers. In: Interspeech 2021. ; 2021. doi:10.21437/interspeech.2021-1177'
apa: 'von Neumann, T., Kinoshita, K., Boeddeker, C., Delcroix, M., & Haeb-Umbach,
R. (2021). Graph-PIT: Generalized Permutation Invariant Training for Continuous
Separation of Arbitrary Numbers of Speakers. Interspeech 2021. Interspeech.
https://doi.org/10.21437/interspeech.2021-1177'
bibtex: '@inproceedings{von Neumann_Kinoshita_Boeddeker_Delcroix_Haeb-Umbach_2021,
title={Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
of Arbitrary Numbers of Speakers}, DOI={10.21437/interspeech.2021-1177},
booktitle={Interspeech 2021}, author={von Neumann, Thilo and Kinoshita, Keisuke
and Boeddeker, Christoph and Delcroix, Marc and Haeb-Umbach, Reinhold}, year={2021}
}'
chicago: 'Neumann, Thilo von, Keisuke Kinoshita, Christoph Boeddeker, Marc Delcroix,
and Reinhold Haeb-Umbach. “Graph-PIT: Generalized Permutation Invariant Training
for Continuous Separation of Arbitrary Numbers of Speakers.” In Interspeech
2021, 2021. https://doi.org/10.21437/interspeech.2021-1177.'
ieee: 'T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach,
“Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
of Arbitrary Numbers of Speakers,” presented at the Interspeech, 2021, doi: 10.21437/interspeech.2021-1177.'
mla: 'von Neumann, Thilo, et al. “Graph-PIT: Generalized Permutation Invariant Training
for Continuous Separation of Arbitrary Numbers of Speakers.” Interspeech 2021,
2021, doi:10.21437/interspeech.2021-1177.'
short: 'T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, R. Haeb-Umbach,
in: Interspeech 2021, 2021.'
conference:
name: Interspeech
date_created: 2021-10-25T08:50:01Z
date_updated: 2023-11-15T12:14:40Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.21437/interspeech.2021-1177
file:
- access_level: open_access
content_type: video/mp4
creator: tvn
date_created: 2021-12-06T10:39:13Z
date_updated: 2021-12-06T10:48:30Z
file_id: '28327'
file_name: Interspeech 2021 voiceover-002-compressed.mp4
file_size: 9550220
relation: supplementary_material
title: Video for INTERSPEECH 2021
- access_level: open_access
content_type: application/vnd.openxmlformats-officedocument.presentationml.presentation
creator: tvn
date_created: 2021-12-06T10:47:01Z
date_updated: 2021-12-06T10:47:01Z
file_id: '28328'
file_name: Graph-PIT-poster-presentation.pptx
file_size: 1337297
relation: slides
title: Slides from INTERSPEECH 2021
- access_level: open_access
content_type: application/pdf
creator: tvn
date_created: 2021-12-06T10:48:21Z
date_updated: 2021-12-06T10:48:21Z
file_id: '28329'
file_name: INTERSPEECH2021_Graph_PIT.pdf
file_size: 226589
relation: main_file
file_date_updated: 2021-12-06T10:48:30Z
has_accepted_license: '1'
keyword:
- Continuous speech separation
- automatic speech recognition
- overlapped speech
- permutation invariant training
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Interspeech 2021
publication_status: published
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/fgnt/graph_pit
status: public
title: 'Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
of Arbitrary Numbers of Speakers'
type: conference
user_id: '49870'
year: '2021'
...
---
_id: '29173'
author:
- first_name: Thilo
full_name: von Neumann, Thilo
id: '49870'
last_name: von Neumann
orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Keisuke
full_name: Kinoshita, Keisuke
last_name: Kinoshita
- first_name: Marc
full_name: Delcroix, Marc
last_name: Delcroix
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'von Neumann T, Boeddeker C, Kinoshita K, Delcroix M, Haeb-Umbach R. Speeding
Up Permutation Invariant Training for Source Separation. In: Speech Communication;
14th ITG Conference. ; 2021.'
apa: von Neumann, T., Boeddeker, C., Kinoshita, K., Delcroix, M., & Haeb-Umbach,
R. (2021). Speeding Up Permutation Invariant Training for Source Separation. Speech
Communication; 14th ITG Conference. Speech Communication; 14th ITG Conference,
Kiel.
bibtex: '@inproceedings{von Neumann_Boeddeker_Kinoshita_Delcroix_Haeb-Umbach_2021,
title={Speeding Up Permutation Invariant Training for Source Separation}, booktitle={Speech
Communication; 14th ITG Conference}, author={von Neumann, Thilo and Boeddeker,
Christoph and Kinoshita, Keisuke and Delcroix, Marc and Haeb-Umbach, Reinhold},
year={2021} }'
chicago: Neumann, Thilo von, Christoph Boeddeker, Keisuke Kinoshita, Marc Delcroix,
and Reinhold Haeb-Umbach. “Speeding Up Permutation Invariant Training for Source
Separation.” In Speech Communication; 14th ITG Conference, 2021.
ieee: T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, and R. Haeb-Umbach,
“Speeding Up Permutation Invariant Training for Source Separation,” presented
at the Speech Communication; 14th ITG Conference, Kiel, 2021.
mla: von Neumann, Thilo, et al. “Speeding Up Permutation Invariant Training for
Source Separation.” Speech Communication; 14th ITG Conference, 2021.
short: 'T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, R. Haeb-Umbach,
in: Speech Communication; 14th ITG Conference, 2021.'
conference:
end_date: 2021-10-01
location: Kiel
name: Speech Communication; 14th ITG Conference
start_date: 2021-09-29
date_created: 2022-01-07T10:40:56Z
date_updated: 2023-11-15T12:16:31Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: tvn
date_created: 2022-01-06T13:23:27Z
date_updated: 2022-01-06T13:23:27Z
file_id: '29180'
file_name: poster.pdf
file_size: 191938
relation: poster
- access_level: open_access
content_type: application/pdf
creator: tvn
date_created: 2022-01-07T10:42:54Z
date_updated: 2022-01-07T10:42:54Z
file_id: '29181'
file_name: ITG2021_Speeding_up_Permutation_Invariant_Training.pdf
file_size: 236670
relation: main_file
file_date_updated: 2022-01-07T10:42:54Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Speech Communication; 14th ITG Conference
quality_controlled: '1'
status: public
title: Speeding Up Permutation Invariant Training for Source Separation
type: conference
user_id: '49870'
year: '2021'
...
---
_id: '29308'
abstract:
- lang: eng
text: 'In this paper we present our system for the Detection and Classification
of Acoustic Scenes and Events (DCASE) 2021 Challenge Task 4: Sound Event Detection
and Separation in Domestic Environments, where it scored the fourth rank. Our
presented solution is an advancement of our system used in the previous edition
of the task.We use a forward-backward convolutional recurrent neural network (FBCRNN)
for tagging and pseudo labeling followed by tag-conditioned sound event detection
(SED) models which are trained using strong pseudo labels provided by the FBCRNN.
Our advancement over our earlier model is threefold. First, we introduce a strong
label loss in the objective of the FBCRNN to take advantage of the strongly labeled
synthetic data during training. Second, we perform multiple iterations of self-training
for both the FBCRNN and tag-conditioned SED models. Third, while we used only
tag-conditioned CNNs as our SED model in the previous edition we here explore
sophisticated tag-conditioned SED model architectures, namely, bidirectional CRNNs
and bidirectional convolutional transformer neural networks (CTNNs), and combine
them. With metric and class specific tuning of median filter lengths for post-processing,
our final SED model, consisting of 6 submodels (2 of each architecture), achieves
on the public evaluation set poly-phonic sound event detection scores (PSDS) of
0.455 for scenario 1 and 0.684 for scenario as well as a collar-based F1-score
of 0.596 outperforming the baselines and our model from the previous edition by
far. Source code is publicly available at https://github.com/fgnt/pb_sed.'
author:
- first_name: Janek
full_name: Ebbers, Janek
id: '34851'
last_name: Ebbers
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ebbers J, Haeb-Umbach R. Self-Trained Audio Tagging and Sound Event Detection
in Domestic Environments. In: Proceedings of the 6th Detection and Classification
of Acoustic Scenes and Events 2021 Workshop (DCASE2021). ; 2021:226–230.'
apa: Ebbers, J., & Haeb-Umbach, R. (2021). Self-Trained Audio Tagging and Sound
Event Detection in Domestic Environments. Proceedings of the 6th Detection
and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021),
226–230.
bibtex: '@inproceedings{Ebbers_Haeb-Umbach_2021, place={Barcelona, Spain}, title={Self-Trained
Audio Tagging and Sound Event Detection in Domestic Environments}, booktitle={Proceedings
of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop
(DCASE2021)}, author={Ebbers, Janek and Haeb-Umbach, Reinhold}, year={2021}, pages={226–230}
}'
chicago: Ebbers, Janek, and Reinhold Haeb-Umbach. “Self-Trained Audio Tagging and
Sound Event Detection in Domestic Environments.” In Proceedings of the 6th
Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021),
226–230. Barcelona, Spain, 2021.
ieee: J. Ebbers and R. Haeb-Umbach, “Self-Trained Audio Tagging and Sound Event
Detection in Domestic Environments,” in Proceedings of the 6th Detection and
Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021), 2021,
pp. 226–230.
mla: Ebbers, Janek, and Reinhold Haeb-Umbach. “Self-Trained Audio Tagging and Sound
Event Detection in Domestic Environments.” Proceedings of the 6th Detection
and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021),
2021, pp. 226–230.
short: 'J. Ebbers, R. Haeb-Umbach, in: Proceedings of the 6th Detection and Classification
of Acoustic Scenes and Events 2021 Workshop (DCASE2021), Barcelona, Spain, 2021,
pp. 226–230.'
date_created: 2022-01-13T08:07:47Z
date_updated: 2023-11-22T08:28:32Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: ebbers
date_created: 2022-01-13T08:08:54Z
date_updated: 2022-01-13T08:19:50Z
file_id: '29309'
file_name: template.pdf
file_size: 239462
relation: main_file
file_date_updated: 2022-01-13T08:19:50Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 226–230
place: Barcelona, Spain
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the 6th Detection and Classification of Acoustic Scenes
and Events 2021 Workshop (DCASE2021)
publication_identifier:
isbn:
- 978-84-09-36072-7
quality_controlled: '1'
status: public
title: Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments
type: conference
user_id: '34851'
year: '2021'
...
---
_id: '29306'
abstract:
- lang: eng
text: Recently, there has been a rising interest in sound recognition via Acoustic
Sensor Networks to support applications such as ambient assisted living or environmental
habitat monitoring. With state-of-the-art sound recognition being dominated by
deep-learning-based approaches, there is a high demand for labeled training data.
Despite the availability of large-scale data sets such as Google's AudioSet,
acquiring training data matching a certain application environment is still often
a problem. In this paper we are concerned with human activity monitoring in a
domestic environment using an ASN consisting of multiple nodes each providing
multichannel signals. We propose a self-training based domain adaptation approach,
which only requires unlabeled data from the target environment. Here, a sound
recognition system trained on AudioSet, the teacher, generates pseudo labels for
data from the target environment on which a student network is trained. The student
can furthermore glean information about the spatial arrangement of sensors and
sound sources to further improve classification performance. It is shown that the
student significantly improves recognition performance over the pre-trained teacher
without relying on labeled data from the environment the system is deployed in.
author:
- first_name: Janek
full_name: Ebbers, Janek
id: '34851'
last_name: Ebbers
- first_name: Moritz Curt
full_name: Keyser, Moritz Curt
last_name: Keyser
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Ebbers J, Keyser MC, Haeb-Umbach R. Adapting Sound Recognition to A New Environment
Via Self-Training. In: Proceedings of the 29th European Signal Processing Conference
(EUSIPCO). ; 2021:1135–1139.'
apa: Ebbers, J., Keyser, M. C., & Haeb-Umbach, R. (2021). Adapting Sound Recognition
to A New Environment Via Self-Training. Proceedings of the 29th European Signal
Processing Conference (EUSIPCO), 1135–1139.
bibtex: '@inproceedings{Ebbers_Keyser_Haeb-Umbach_2021, title={Adapting Sound Recognition
to A New Environment Via Self-Training}, booktitle={Proceedings of the 29th European
Signal Processing Conference (EUSIPCO)}, author={Ebbers, Janek and Keyser, Moritz
Curt and Haeb-Umbach, Reinhold}, year={2021}, pages={1135–1139} }'
chicago: Ebbers, Janek, Moritz Curt Keyser, and Reinhold Haeb-Umbach. “Adapting
Sound Recognition to A New Environment Via Self-Training.” In Proceedings of
the 29th European Signal Processing Conference (EUSIPCO), 1135–1139, 2021.
ieee: J. Ebbers, M. C. Keyser, and R. Haeb-Umbach, “Adapting Sound Recognition to
A New Environment Via Self-Training,” in Proceedings of the 29th European Signal
Processing Conference (EUSIPCO), 2021, pp. 1135–1139.
mla: Ebbers, Janek, et al. “Adapting Sound Recognition to A New Environment Via
Self-Training.” Proceedings of the 29th European Signal Processing Conference
(EUSIPCO), 2021, pp. 1135–1139.
short: 'J. Ebbers, M.C. Keyser, R. Haeb-Umbach, in: Proceedings of the 29th European
Signal Processing Conference (EUSIPCO), 2021, pp. 1135–1139.'
date_created: 2022-01-13T08:01:21Z
date_updated: 2023-11-22T08:28:50Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: ebbers
date_created: 2022-01-13T08:03:26Z
date_updated: 2022-01-13T08:19:35Z
file_id: '29307'
file_name: conference_101719.pdf
file_size: 213938
relation: main_file
file_date_updated: 2022-01-13T08:19:35Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 1135–1139
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Proceedings of the 29th European Signal Processing Conference (EUSIPCO)
quality_controlled: '1'
status: public
title: Adapting Sound Recognition to A New Environment Via Self-Training
type: conference
user_id: '34851'
year: '2021'
...
---
_id: '24456'
abstract:
- lang: eng
text: One objective of current research in explainable intelligent systems is to
implement social aspects in order to increase the relevance of explanations. In
this paper, we argue that a novel conceptual framework is needed to overcome shortcomings
of existing AI systems with little attention to processes of interaction and learning.
Drawing from research in interaction and development, we first outline the novel
conceptual framework that pushes the design of AI systems toward true interactivity
with an emphasis on the role of the partner and social relevance. We propose that
AI systems will be able to provide a meaningful and relevant explanation only
if the process of explaining is extended to active contribution of both partners
that brings about dynamics that is modulated by different levels of analysis.
Accordingly, our conceptual framework comprises monitoring and scaffolding as
key concepts and claims that the process of explaining is not only modulated by
the interaction between explainee and explainer but is embedded into a larger
social context in which conventionalized and routinized behaviors are established.
We discuss our conceptual framework in relation to the established objectives
of transparency and autonomy that are raised for the design of explainable AI
systems currently.
article_type: original
author:
- first_name: Katharina J.
full_name: Rohlfing, Katharina J.
id: '50352'
last_name: Rohlfing
- first_name: Philipp
full_name: Cimiano, Philipp
last_name: Cimiano
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
- first_name: Tobias
full_name: Matzner, Tobias
id: '65695'
last_name: Matzner
- first_name: Heike M.
full_name: Buhl, Heike M.
id: '27152'
last_name: Buhl
- first_name: Hendrik
full_name: Buschmeier, Hendrik
last_name: Buschmeier
- first_name: Elena
full_name: Esposito, Elena
last_name: Esposito
- first_name: Angela
full_name: Grimminger, Angela
id: '57578'
last_name: Grimminger
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
- first_name: Ilona
full_name: Horwath, Ilona
id: '68836'
last_name: Horwath
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Friederike
full_name: Kern, Friederike
last_name: Kern
- first_name: Stefan
full_name: Kopp, Stefan
last_name: Kopp
- first_name: Kirsten
full_name: Thommes, Kirsten
id: '72497'
last_name: Thommes
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Carsten
full_name: Schulte, Carsten
id: '60311'
last_name: Schulte
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Petra
full_name: Wagner, Petra
last_name: Wagner
- first_name: Britta
full_name: Wrede, Britta
last_name: Wrede
citation:
ama: 'Rohlfing KJ, Cimiano P, Scharlau I, et al. Explanation as a Social Practice:
Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions
on Cognitive and Developmental Systems. 2021;13(3):717-728. doi:10.1109/tcds.2020.3044366'
apa: 'Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier,
H., Esposito, E., Grimminger, A., Hammer, B., Haeb-Umbach, R., Horwath, I., Hüllermeier,
E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A.-C., Schulte, C., Wachsmuth,
H., Wagner, P., & Wrede, B. (2021). Explanation as a Social Practice: Toward
a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions
on Cognitive and Developmental Systems, 13(3), 717–728. https://doi.org/10.1109/tcds.2020.3044366'
bibtex: '@article{Rohlfing_Cimiano_Scharlau_Matzner_Buhl_Buschmeier_Esposito_Grimminger_Hammer_Haeb-Umbach_et
al._2021, title={Explanation as a Social Practice: Toward a Conceptual Framework
for the Social Design of AI Systems}, volume={13}, DOI={10.1109/tcds.2020.3044366},
number={3}, journal={IEEE Transactions on Cognitive and Developmental Systems},
author={Rohlfing, Katharina J. and Cimiano, Philipp and Scharlau, Ingrid and Matzner,
Tobias and Buhl, Heike M. and Buschmeier, Hendrik and Esposito, Elena and Grimminger,
Angela and Hammer, Barbara and Haeb-Umbach, Reinhold and et al.}, year={2021},
pages={717–728} }'
chicago: 'Rohlfing, Katharina J., Philipp Cimiano, Ingrid Scharlau, Tobias Matzner,
Heike M. Buhl, Hendrik Buschmeier, Elena Esposito, et al. “Explanation as a Social
Practice: Toward a Conceptual Framework for the Social Design of AI Systems.”
IEEE Transactions on Cognitive and Developmental Systems 13, no. 3 (2021):
717–28. https://doi.org/10.1109/tcds.2020.3044366.'
ieee: 'K. J. Rohlfing et al., “Explanation as a Social Practice: Toward a
Conceptual Framework for the Social Design of AI Systems,” IEEE Transactions
on Cognitive and Developmental Systems, vol. 13, no. 3, pp. 717–728, 2021,
doi: 10.1109/tcds.2020.3044366.'
mla: 'Rohlfing, Katharina J., et al. “Explanation as a Social Practice: Toward a
Conceptual Framework for the Social Design of AI Systems.” IEEE Transactions
on Cognitive and Developmental Systems, vol. 13, no. 3, 2021, pp. 717–28,
doi:10.1109/tcds.2020.3044366.'
short: K.J. Rohlfing, P. Cimiano, I. Scharlau, T. Matzner, H.M. Buhl, H. Buschmeier,
E. Esposito, A. Grimminger, B. Hammer, R. Haeb-Umbach, I. Horwath, E. Hüllermeier,
F. Kern, S. Kopp, K. Thommes, A.-C. Ngonga Ngomo, C. Schulte, H. Wachsmuth, P.
Wagner, B. Wrede, IEEE Transactions on Cognitive and Developmental Systems 13
(2021) 717–728.
date_created: 2021-09-14T20:52:57Z
date_updated: 2023-12-05T10:15:02Z
ddc:
- '300'
department:
- _id: '603'
- _id: '749'
- _id: '424'
- _id: '67'
- _id: '574'
- _id: '184'
- _id: '757'
- _id: '54'
- _id: '178'
doi: 10.1109/tcds.2020.3044366
file:
- access_level: open_access
content_type: application/pdf
creator: haebumb
date_created: 2023-11-20T16:33:51Z
date_updated: 2023-11-20T16:33:51Z
file_id: '49081'
file_name: 2020-12-01_explainability_final_version.pdf
file_size: 626217
relation: main_file
file_date_updated: 2023-11-20T16:33:51Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '3'
keyword:
- Explainability
- process ofexplaining andunderstanding
- explainable artificial systems
language:
- iso: eng
oa: '1'
page: 717-728
project:
- _id: '109'
grant_number: '438445824'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
publication: IEEE Transactions on Cognitive and Developmental Systems
publication_identifier:
issn:
- 2379-8920
- 2379-8939
publication_status: published
quality_controlled: '1'
status: public
title: 'Explanation as a Social Practice: Toward a Conceptual Framework for the Social
Design of AI Systems'
type: journal_article
user_id: '42933'
volume: 13
year: '2021'
...
---
_id: '17763'
author:
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Haeb-Umbach R. Sprachtechnologien für Digitale Assistenten. In: Böck R, Siegert
I, Wendemuth A, eds. Studientexte Zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung
2020. TUDpress, Dresden; 2020:227-234.'
apa: 'Haeb-Umbach, R. (2020). Sprachtechnologien für Digitale Assistenten. In R.
Böck, I. Siegert, & A. Wendemuth (Eds.), Studientexte zur Sprachkommunikation:
Elektronische Sprachsignalverarbeitung 2020 (pp. 227–234). TUDpress, Dresden.'
bibtex: '@inproceedings{Haeb-Umbach_2020, title={Sprachtechnologien für Digitale
Assistenten}, booktitle={Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung
2020}, publisher={TUDpress, Dresden}, author={Haeb-Umbach, Reinhold}, editor={Böck,
Ronald and Siegert, Ingo and Wendemuth, AndreasEditors}, year={2020}, pages={227–234}
}'
chicago: 'Haeb-Umbach, Reinhold. “Sprachtechnologien Für Digitale Assistenten.”
In Studientexte Zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung
2020, edited by Ronald Böck, Ingo Siegert, and Andreas Wendemuth, 227–34.
TUDpress, Dresden, 2020.'
ieee: 'R. Haeb-Umbach, “Sprachtechnologien für Digitale Assistenten,” in Studientexte
zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020, 2020,
pp. 227–234.'
mla: 'Haeb-Umbach, Reinhold. “Sprachtechnologien Für Digitale Assistenten.” Studientexte
Zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020, edited
by Ronald Böck et al., TUDpress, Dresden, 2020, pp. 227–34.'
short: 'R. Haeb-Umbach, in: R. Böck, I. Siegert, A. Wendemuth (Eds.), Studientexte
Zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020, TUDpress,
Dresden, 2020, pp. 227–234.'
date_created: 2020-08-10T09:53:12Z
date_updated: 2022-01-06T06:53:19Z
department:
- _id: '54'
editor:
- first_name: Ronald
full_name: Böck, Ronald
last_name: Böck
- first_name: Ingo
full_name: Siegert, Ingo
last_name: Siegert
- first_name: Andreas
full_name: Wendemuth, Andreas
last_name: Wendemuth
keyword:
- Poster
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2020/ESSV_2020_haeb_umbach.pdf
oa: '1'
page: 227-234
publication: 'Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung
2020'
publication_identifier:
isbn:
- 978-3-959081-93-1
publisher: TUDpress, Dresden
status: public
title: Sprachtechnologien für Digitale Assistenten
type: conference
user_id: '44006'
year: '2020'
...
---
_id: '20700'
author:
- first_name: Christoph
full_name: Boeddeker, Christoph
id: '40767'
last_name: Boeddeker
- first_name: Tobias
full_name: Cord-Landwehr, Tobias
id: '44393'
last_name: Cord-Landwehr
- first_name: Jens
full_name: Heitkaemper, Jens
id: '27643'
last_name: Heitkaemper
- first_name: Catalin
full_name: Zorila, Catalin
last_name: Zorila
- first_name: Daichi
full_name: Hayakawa, Daichi
last_name: Hayakawa
- first_name: Mohan
full_name: Li, Mohan
last_name: Li
- first_name: Min
full_name: Liu, Min
last_name: Liu
- first_name: Rama
full_name: Doddipatla, Rama
last_name: Doddipatla
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Boeddeker C, Cord-Landwehr T, Heitkaemper J, et al. Towards a speaker diarization
system for the CHiME 2020 dinner party transcription. In: Proc. CHiME 2020
Workshop on Speech Processing in Everyday Environments. ; 2020.'
apa: Boeddeker, C., Cord-Landwehr, T., Heitkaemper, J., Zorila, C., Hayakawa, D.,
Li, M., … Haeb-Umbach, R. (2020). Towards a speaker diarization system for the
CHiME 2020 dinner party transcription. In Proc. CHiME 2020 Workshop on Speech
Processing in Everyday Environments.
bibtex: '@inproceedings{Boeddeker_Cord-Landwehr_Heitkaemper_Zorila_Hayakawa_Li_Liu_Doddipatla_Haeb-Umbach_2020,
title={Towards a speaker diarization system for the CHiME 2020 dinner party transcription},
booktitle={Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments},
author={Boeddeker, Christoph and Cord-Landwehr, Tobias and Heitkaemper, Jens and
Zorila, Catalin and Hayakawa, Daichi and Li, Mohan and Liu, Min and Doddipatla,
Rama and Haeb-Umbach, Reinhold}, year={2020} }'
chicago: Boeddeker, Christoph, Tobias Cord-Landwehr, Jens Heitkaemper, Catalin Zorila,
Daichi Hayakawa, Mohan Li, Min Liu, Rama Doddipatla, and Reinhold Haeb-Umbach.
“Towards a Speaker Diarization System for the CHiME 2020 Dinner Party Transcription.”
In Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments,
2020.
ieee: C. Boeddeker et al., “Towards a speaker diarization system for the
CHiME 2020 dinner party transcription,” in Proc. CHiME 2020 Workshop on Speech
Processing in Everyday Environments, 2020.
mla: Boeddeker, Christoph, et al. “Towards a Speaker Diarization System for the
CHiME 2020 Dinner Party Transcription.” Proc. CHiME 2020 Workshop on Speech
Processing in Everyday Environments, 2020.
short: 'C. Boeddeker, T. Cord-Landwehr, J. Heitkaemper, C. Zorila, D. Hayakawa,
M. Li, M. Liu, R. Doddipatla, R. Haeb-Umbach, in: Proc. CHiME 2020 Workshop on
Speech Processing in Everyday Environments, 2020.'
date_created: 2020-12-11T12:49:13Z
date_updated: 2022-01-06T06:54:33Z
ddc:
- '000'
department:
- _id: '54'
file:
- access_level: open_access
content_type: application/pdf
creator: cbj
date_created: 2020-12-11T12:48:48Z
date_updated: 2020-12-11T12:48:48Z
file_id: '20702'
file_name: template.pdf
file_size: 115421
relation: main_file
file_date_updated: 2020-12-11T12:48:48Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments
status: public
title: Towards a speaker diarization system for the CHiME 2020 dinner party transcription
type: conference
user_id: '40767'
year: '2020'
...