Anantha K. Karthik, Rick S. Blum
{"title":"分组交换网络时钟同步研究进展","authors":"Anantha K. Karthik, Rick S. Blum","doi":"10.1561/2000000108","DOIUrl":null,"url":null,"abstract":"Speech enhancement is a core problem in audio signal processing with commercial applications in devices as diverse as mobile phones, conference call systems, smart assistants, and hearing aids. An essential component in the design of speech enhancement algorithms is acoustic source localization. Speaker localization is also directly applicable to many other audio related tasks, e.g., automated camera steering, teleconferencing systems, and robot audition. From a signal processing perspective, speaker localization is the task of mapping multichannel speech signals to 3-D source coordinates. To obtain viable solutions for this mapping, an accurate description of the source wave propagation captured by the respective acoustic channel is required. In fact, the acoustic channels can be considered as the spatial fingerprints characterizing the positions of each of the sources in a reverberant enclosure. These fingerprints represent complex reflection patterns stemming from the surfaces and objects characterizing the enclosure. Hence, they are Bracha Laufer-Goldshtein, Ronen Talmon and Sharon Gannot (2020), “Data-Driven Multi-Microphone Speaker Localization on Manifolds”, Foundations and Trends © in Signal Processing: Vol. 14, No. 1–2, pp 1–161. DOI: 10.1561/2000000098. Full text available at: http://dx.doi.org/10.1561/2000000098","PeriodicalId":12340,"journal":{"name":"Found. Trends Signal Process.","volume":"5 1","pages":"360-443"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Recent Advances in Clock Synchronization for Packet-Switched Networks\",\"authors\":\"Anantha K. Karthik, Rick S. Blum\",\"doi\":\"10.1561/2000000108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Speech enhancement is a core problem in audio signal processing with commercial applications in devices as diverse as mobile phones, conference call systems, smart assistants, and hearing aids. An essential component in the design of speech enhancement algorithms is acoustic source localization. Speaker localization is also directly applicable to many other audio related tasks, e.g., automated camera steering, teleconferencing systems, and robot audition. From a signal processing perspective, speaker localization is the task of mapping multichannel speech signals to 3-D source coordinates. To obtain viable solutions for this mapping, an accurate description of the source wave propagation captured by the respective acoustic channel is required. In fact, the acoustic channels can be considered as the spatial fingerprints characterizing the positions of each of the sources in a reverberant enclosure. These fingerprints represent complex reflection patterns stemming from the surfaces and objects characterizing the enclosure. Hence, they are Bracha Laufer-Goldshtein, Ronen Talmon and Sharon Gannot (2020), “Data-Driven Multi-Microphone Speaker Localization on Manifolds”, Foundations and Trends © in Signal Processing: Vol. 14, No. 1–2, pp 1–161. DOI: 10.1561/2000000098. Full text available at: http://dx.doi.org/10.1561/2000000098\",\"PeriodicalId\":12340,\"journal\":{\"name\":\"Found. Trends Signal Process.\",\"volume\":\"5 1\",\"pages\":\"360-443\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Found. Trends Signal Process.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1561/2000000108\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Found. Trends Signal Process.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1561/2000000108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Recent Advances in Clock Synchronization for Packet-Switched Networks
Speech enhancement is a core problem in audio signal processing with commercial applications in devices as diverse as mobile phones, conference call systems, smart assistants, and hearing aids. An essential component in the design of speech enhancement algorithms is acoustic source localization. Speaker localization is also directly applicable to many other audio related tasks, e.g., automated camera steering, teleconferencing systems, and robot audition. From a signal processing perspective, speaker localization is the task of mapping multichannel speech signals to 3-D source coordinates. To obtain viable solutions for this mapping, an accurate description of the source wave propagation captured by the respective acoustic channel is required. In fact, the acoustic channels can be considered as the spatial fingerprints characterizing the positions of each of the sources in a reverberant enclosure. These fingerprints represent complex reflection patterns stemming from the surfaces and objects characterizing the enclosure. Hence, they are Bracha Laufer-Goldshtein, Ronen Talmon and Sharon Gannot (2020), “Data-Driven Multi-Microphone Speaker Localization on Manifolds”, Foundations and Trends © in Signal Processing: Vol. 14, No. 1–2, pp 1–161. DOI: 10.1561/2000000098. Full text available at: http://dx.doi.org/10.1561/2000000098