--- _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' ...