{"title":"先进的语音活动检测手机上使用麦克风阵列和音素特定的高斯混合模型","authors":"B. Popović, E. Pakoci, D. Pekar","doi":"10.1109/SISY.2016.7601516","DOIUrl":null,"url":null,"abstract":"This paper presents an advanced voice activity detection (VAD) system, developed for mobile Android OS platforms with limited hardware capabilities. The system uses a dual microphone array for noise suppression and a decoder with a constrained grammar for speech detection, where Gaussian mixture models (GMMs) are used together with their acoustic weights and energy in order to increase the robustness of the proposed system. The system is presented as part of the Voice Assistant application for mobile phones, and the results are given on a database that was especially designed for that purpose. The results presented in this paper show a high accuracy even when a large amount of background noise is present.","PeriodicalId":193153,"journal":{"name":"2016 IEEE 14th International Symposium on Intelligent Systems and Informatics (SISY)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Advanced voice activity detection on mobile phones by using microphone array and phoneme-specific Gaussian mixture models\",\"authors\":\"B. Popović, E. Pakoci, D. Pekar\",\"doi\":\"10.1109/SISY.2016.7601516\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an advanced voice activity detection (VAD) system, developed for mobile Android OS platforms with limited hardware capabilities. The system uses a dual microphone array for noise suppression and a decoder with a constrained grammar for speech detection, where Gaussian mixture models (GMMs) are used together with their acoustic weights and energy in order to increase the robustness of the proposed system. The system is presented as part of the Voice Assistant application for mobile phones, and the results are given on a database that was especially designed for that purpose. The results presented in this paper show a high accuracy even when a large amount of background noise is present.\",\"PeriodicalId\":193153,\"journal\":{\"name\":\"2016 IEEE 14th International Symposium on Intelligent Systems and Informatics (SISY)\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 14th International Symposium on Intelligent Systems and Informatics (SISY)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SISY.2016.7601516\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 14th International Symposium on Intelligent Systems and Informatics (SISY)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SISY.2016.7601516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Advanced voice activity detection on mobile phones by using microphone array and phoneme-specific Gaussian mixture models
This paper presents an advanced voice activity detection (VAD) system, developed for mobile Android OS platforms with limited hardware capabilities. The system uses a dual microphone array for noise suppression and a decoder with a constrained grammar for speech detection, where Gaussian mixture models (GMMs) are used together with their acoustic weights and energy in order to increase the robustness of the proposed system. The system is presented as part of the Voice Assistant application for mobile phones, and the results are given on a database that was especially designed for that purpose. The results presented in this paper show a high accuracy even when a large amount of background noise is present.