{"title":"基于相干态的非持续声活动无线声传感器网络的长期同步","authors":"Aleksej Chinaev, Niklas Knaepper, G. Enzner","doi":"10.1109/ICASSP49357.2023.10095792","DOIUrl":null,"url":null,"abstract":"Sample-accurate synchronization of nodes is required to enable the full potential of acoustic sensor networks for cooperative and enhanced signal acquisition. While metrics of spatio-temporal sensor utility are key to successful aggregation of sensor nodes, for instance, to perform sound localization or beamforming, the same is true for waveform-based assessment and compensation of sampling-rate offset (SRO). This paper therefore proposes an acoustic coherence state (ACS) metric to support systems for SRO estimation to integrate estimations of various utility due to nonpersistent acoustic activity and geometrical diversity. Specifically, we consider systems with SRO estimation and compensation in open- and closed-loop structures and outline the architectures for embedding ACS-based sensor utility. It is demonstrated in both cases that the acoustic coherence metric is more appropriate in terms of end-to-end synchronization performance than voice or sound activity detectors.","PeriodicalId":113072,"journal":{"name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Long-Term Synchronization of Wireless Acoustic Sensor Networks with Nonpersistent Acoustic Activity Using Coherence State\",\"authors\":\"Aleksej Chinaev, Niklas Knaepper, G. Enzner\",\"doi\":\"10.1109/ICASSP49357.2023.10095792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sample-accurate synchronization of nodes is required to enable the full potential of acoustic sensor networks for cooperative and enhanced signal acquisition. While metrics of spatio-temporal sensor utility are key to successful aggregation of sensor nodes, for instance, to perform sound localization or beamforming, the same is true for waveform-based assessment and compensation of sampling-rate offset (SRO). This paper therefore proposes an acoustic coherence state (ACS) metric to support systems for SRO estimation to integrate estimations of various utility due to nonpersistent acoustic activity and geometrical diversity. Specifically, we consider systems with SRO estimation and compensation in open- and closed-loop structures and outline the architectures for embedding ACS-based sensor utility. It is demonstrated in both cases that the acoustic coherence metric is more appropriate in terms of end-to-end synchronization performance than voice or sound activity detectors.\",\"PeriodicalId\":113072,\"journal\":{\"name\":\"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP49357.2023.10095792\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP49357.2023.10095792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Long-Term Synchronization of Wireless Acoustic Sensor Networks with Nonpersistent Acoustic Activity Using Coherence State
Sample-accurate synchronization of nodes is required to enable the full potential of acoustic sensor networks for cooperative and enhanced signal acquisition. While metrics of spatio-temporal sensor utility are key to successful aggregation of sensor nodes, for instance, to perform sound localization or beamforming, the same is true for waveform-based assessment and compensation of sampling-rate offset (SRO). This paper therefore proposes an acoustic coherence state (ACS) metric to support systems for SRO estimation to integrate estimations of various utility due to nonpersistent acoustic activity and geometrical diversity. Specifically, we consider systems with SRO estimation and compensation in open- and closed-loop structures and outline the architectures for embedding ACS-based sensor utility. It is demonstrated in both cases that the acoustic coherence metric is more appropriate in terms of end-to-end synchronization performance than voice or sound activity detectors.