{"title":"Web Service-Based Turkish Automatic Speech Recognition Platform","authors":"Saadin Oyucu, Hüseyin Polat, H. Sever","doi":"10.1109/HORA49412.2020.9152920","DOIUrl":null,"url":null,"abstract":"In response to the similar challenges in building large-scale distributed applications and platforms on the Web, microservice architecture has emerged and gained a lot of popularity in recent years. Therefore, both for the use of microservices and for the provided of the necessary interface for Automatic Speech Recognition (ASR), a web-based platform has been developed. Within firstly the scope of the study, a Turkish ASR system was developed. A web service structure was created to facilitate access to the ASR system. The access of methods and data in the web service structure was provided through Representational State Transfer (REST) web services and service layer. An interface was developed to enable interaction with the web service. The platform was developed using a combination of different technologies such as ASR, web services, microservices, and interface technologies. The developed platform can be used via a standard web browser or an Application Programming Interface (API). In this study, Docker packages were used to improve system performance instead of using different virtual machines on a single server. In the experiments performed, it was shown that the Turkish ASR system had a word error rate of 24.70%. In web service performance tests, it was shown that the platform responded in an average of 9.6 seconds for a 59-second speech recording. The developed user interface was tested in both mobile and desktop web browsers and was shown to function properly. Applications and other services were given access to the platform without the need to use an interface via API support provided by the platform. As a result, a web service-based Turkish ASR platform working seamlessly on the ever-increasing number of mobile devices, the Internet of Things ecosystem, or other access devices was developed.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"03 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HORA49412.2020.9152920","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In response to the similar challenges in building large-scale distributed applications and platforms on the Web, microservice architecture has emerged and gained a lot of popularity in recent years. Therefore, both for the use of microservices and for the provided of the necessary interface for Automatic Speech Recognition (ASR), a web-based platform has been developed. Within firstly the scope of the study, a Turkish ASR system was developed. A web service structure was created to facilitate access to the ASR system. The access of methods and data in the web service structure was provided through Representational State Transfer (REST) web services and service layer. An interface was developed to enable interaction with the web service. The platform was developed using a combination of different technologies such as ASR, web services, microservices, and interface technologies. The developed platform can be used via a standard web browser or an Application Programming Interface (API). In this study, Docker packages were used to improve system performance instead of using different virtual machines on a single server. In the experiments performed, it was shown that the Turkish ASR system had a word error rate of 24.70%. In web service performance tests, it was shown that the platform responded in an average of 9.6 seconds for a 59-second speech recording. The developed user interface was tested in both mobile and desktop web browsers and was shown to function properly. Applications and other services were given access to the platform without the need to use an interface via API support provided by the platform. As a result, a web service-based Turkish ASR platform working seamlessly on the ever-increasing number of mobile devices, the Internet of Things ecosystem, or other access devices was developed.
为了应对在Web上构建大规模分布式应用程序和平台的类似挑战,近年来微服务架构已经出现并获得了广泛的流行。因此,为了使用微服务和为自动语音识别(ASR)提供必要的接口,已经开发了一个基于web的平台。首先,在研究范围内,开发了土耳其ASR系统。创建了一个web服务结构以方便对ASR系统的访问。通过Representational State Transfer (REST) web服务和服务层提供对web服务结构中方法和数据的访问。开发了一个接口来支持与web服务的交互。该平台的开发结合了不同的技术,如ASR、web服务、微服务和接口技术。开发的平台可以通过标准的web浏览器或应用程序编程接口(API)使用。在本研究中,使用Docker包来提高系统性能,而不是在单个服务器上使用不同的虚拟机。实验表明,土耳其语ASR系统的单词错误率为24.70%。在web服务性能测试中,对于59秒的语音录制,平台的平均响应时间为9.6秒。开发的用户界面在移动和桌面网络浏览器上进行了测试,结果显示功能正常。应用程序和其他服务可以访问该平台,而无需通过平台提供的API支持使用接口。因此,基于web服务的土耳其ASR平台可以在数量不断增加的移动设备、物联网生态系统或其他接入设备上无缝工作。