{"title":"语音日记:一种基于语音命令的地面真相收集系统,用于活动识别","authors":"Enamul Hoque, Robert F. Dickerson, J. Stankovic","doi":"10.1145/2668883.2669587","DOIUrl":null,"url":null,"abstract":"We present Vocal-Diary, a voice command based ground truth collection system that uses grammar based commands from residents to log start and end of activities. Vocal-Diary ensures robustness in the presence of sounds from different environmental noise and day-to-day conversation by using two-way acknowledgement and integrating speaker recognition in the pipeline. Vocal-Diary also utilizes the sensor data produced by the underlying activity recognition system to query residents periodically to check if they forgot to log any activity. Evaluation shows that Vocal-Diary increases precision by at least 40% and recall by at least 10% compared to a system that uses voice command recognition without any acknowledgement and speaker recognition.","PeriodicalId":185800,"journal":{"name":"Proceedings of the Wireless Health 2014 on National Institutes of Health","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Vocal-Diary: A Voice Command based Ground Truth Collection System for Activity Recognition\",\"authors\":\"Enamul Hoque, Robert F. Dickerson, J. Stankovic\",\"doi\":\"10.1145/2668883.2669587\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present Vocal-Diary, a voice command based ground truth collection system that uses grammar based commands from residents to log start and end of activities. Vocal-Diary ensures robustness in the presence of sounds from different environmental noise and day-to-day conversation by using two-way acknowledgement and integrating speaker recognition in the pipeline. Vocal-Diary also utilizes the sensor data produced by the underlying activity recognition system to query residents periodically to check if they forgot to log any activity. Evaluation shows that Vocal-Diary increases precision by at least 40% and recall by at least 10% compared to a system that uses voice command recognition without any acknowledgement and speaker recognition.\",\"PeriodicalId\":185800,\"journal\":{\"name\":\"Proceedings of the Wireless Health 2014 on National Institutes of Health\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Wireless Health 2014 on National Institutes of Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2668883.2669587\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Wireless Health 2014 on National Institutes of Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2668883.2669587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vocal-Diary: A Voice Command based Ground Truth Collection System for Activity Recognition
We present Vocal-Diary, a voice command based ground truth collection system that uses grammar based commands from residents to log start and end of activities. Vocal-Diary ensures robustness in the presence of sounds from different environmental noise and day-to-day conversation by using two-way acknowledgement and integrating speaker recognition in the pipeline. Vocal-Diary also utilizes the sensor data produced by the underlying activity recognition system to query residents periodically to check if they forgot to log any activity. Evaluation shows that Vocal-Diary increases precision by at least 40% and recall by at least 10% compared to a system that uses voice command recognition without any acknowledgement and speaker recognition.