{"title":"A Reporting Assistant for Railway Security Staff","authors":"Linglong Meng, Stefan Schaffer","doi":"10.1145/3405755.3406164","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce RARSS, a reporting assistant for railway security staff. RARSS is a demonstration application with a multi-modal interface based on the Mobile Multimodal Interaction and Rendering (MMIR) framework. The system should support the security staff at railway premises (stations, trains, etc.) in Germany and inform about security relevant information about the travel of football fans or a group of people on their way to a major event. In the application we leverage multi keyword spotting (KWS) for detecting of the actual context and a grammar with specific voice commands to improve the semantic interpretation. The results of friendly user testing showed that the multimodal conversational interface was positively rated according the simplicity and the efficiency to make security reports by the security staff.","PeriodicalId":380130,"journal":{"name":"Proceedings of the 2nd Conference on Conversational User Interfaces","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd Conference on Conversational User Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3405755.3406164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we introduce RARSS, a reporting assistant for railway security staff. RARSS is a demonstration application with a multi-modal interface based on the Mobile Multimodal Interaction and Rendering (MMIR) framework. The system should support the security staff at railway premises (stations, trains, etc.) in Germany and inform about security relevant information about the travel of football fans or a group of people on their way to a major event. In the application we leverage multi keyword spotting (KWS) for detecting of the actual context and a grammar with specific voice commands to improve the semantic interpretation. The results of friendly user testing showed that the multimodal conversational interface was positively rated according the simplicity and the efficiency to make security reports by the security staff.