---
_id: '25281'
abstract:
- lang: eng
text: "Wireless Acoustic Sensor Networks (WASNs) have a wide range of audio signal
processing applications. Due to the spatial diversity of the microphone and their
relative position to the acoustic source, not all microphones are equally useful
for subsequent audio signal processing tasks, nor do they all have the same wireless
data transmission rates. Hence, a central task in WASNs is to balance a microphone’s
estimated acoustic utility against its transmission delay, selecting a best-possible
subset of microphones to record audio signals.\r\n\r\nIn this work, we use reinforcement
learning to decide if a microphone should be used or switched off to maximize
the acoustic quality at low transmission delays, while minimizing switching frequency.
In experiments with moving sources in a simulated acoustic environment, our method
outperforms naive baseline comparisons"
author:
- first_name: Haitham
full_name: Afifi, Haitham
id: '65718'
last_name: Afifi
- first_name: Michael
full_name: Guenther, Michael
last_name: Guenther
- first_name: Andreas
full_name: Brendel, Andreas
last_name: Brendel
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
- first_name: Walter
full_name: Kellermann, Walter
last_name: Kellermann
citation:
ama: 'Afifi H, Guenther M, Brendel A, Karl H, Kellermann W. Reinforcement Learning-based
Microphone Selection in Wireless Acoustic Sensor Networks considering Network
and Acoustic Utilities. In: 14. ITG Conference on Speech Communication (ITG
2021). ; 2021.'
apa: Afifi, H., Guenther, M., Brendel, A., Karl, H., & Kellermann, W. (2021).
Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor
Networks considering Network and Acoustic Utilities. 14. ITG Conference on
Speech Communication (ITG 2021).
bibtex: '@inproceedings{Afifi_Guenther_Brendel_Karl_Kellermann_2021, title={Reinforcement
Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering
Network and Acoustic Utilities}, booktitle={14. ITG Conference on Speech Communication
(ITG 2021)}, author={Afifi, Haitham and Guenther, Michael and Brendel, Andreas
and Karl, Holger and Kellermann, Walter}, year={2021} }'
chicago: Afifi, Haitham, Michael Guenther, Andreas Brendel, Holger Karl, and Walter
Kellermann. “Reinforcement Learning-Based Microphone Selection in Wireless Acoustic
Sensor Networks Considering Network and Acoustic Utilities.” In 14. ITG Conference
on Speech Communication (ITG 2021), 2021.
ieee: H. Afifi, M. Guenther, A. Brendel, H. Karl, and W. Kellermann, “Reinforcement
Learning-based Microphone Selection in Wireless Acoustic Sensor Networks considering
Network and Acoustic Utilities,” 2021.
mla: Afifi, Haitham, et al. “Reinforcement Learning-Based Microphone Selection in
Wireless Acoustic Sensor Networks Considering Network and Acoustic Utilities.”
14. ITG Conference on Speech Communication (ITG 2021), 2021.
short: 'H. Afifi, M. Guenther, A. Brendel, H. Karl, W. Kellermann, in: 14. ITG Conference
on Speech Communication (ITG 2021), 2021.'
date_created: 2021-10-04T10:59:50Z
date_updated: 2022-01-06T06:56:59Z
ddc:
- '620'
file:
- access_level: closed
content_type: application/pdf
creator: hafifi
date_created: 2021-10-04T10:58:07Z
date_updated: 2021-10-04T10:58:07Z
file_id: '25282'
file_name: ITG_2021_paper_26 (3).pdf
file_size: 283616
relation: main_file
success: 1
file_date_updated: 2021-10-04T10:58:07Z
has_accepted_license: '1'
keyword:
- microphone utility
- microphone selection
- wireless acoustic sensor network
- network delay
- reinforcement learning
language:
- iso: eng
project:
- _id: '27'
name: Akustische Sensornetzwerke - Teilprojekt "Verteilte akustische Signalverarbeitung
über funkbasierte Sensornetzwerke
publication: 14. ITG Conference on Speech Communication (ITG 2021)
status: public
title: Reinforcement Learning-based Microphone Selection in Wireless Acoustic Sensor
Networks considering Network and Acoustic Utilities
type: conference
user_id: '65718'
year: '2021'
...