Distributed Speaker Recognition Using the ETSI Distributed Speech Recognition Standard
نویسندگان
چکیده
Biometrics is gaining strong support for the personalization of and the securing of mobile devices. It is not uncommon for individual users to be faced with a half-dozen or more passwords and personal identification numbers. The ubiquity of passwords actually relaxes system security since many users tend to use the same password across all applications, or collect the various passwords in a single location. The use of biometrics not only recovers the ability to secure sensitive systems and data, but also does so in a user-friendly manner. The successful use of biometrics in distributed systems addresses several key concerns. First, the authentication strategy must maintain acceptable levels of security. Second, the user community must accept the chosen biometric. The last major consideration is the scalability of the solution. We introduce a biometric access control solution for distributed, mobile computing environments.
منابع مشابه
Distributed Speaker Recognition Using the Etsi Aurora Standard
The ETSI “Aurora” is a standard for distributed speech recognition over the mobile cellular network. We have investigated the use of the features defined in this standard for speaker recognition, in a text-independent system based on Gaussian Mixture Models (GMM). The application context is distributed speaker recognition for user authentication on the mobile cellular network. We have found tha...
متن کاملSpeaker recognition and the ETSI Standard Distributed Speech Recognition Front-End
With the advent of Wireless Application Protocol (WAP) and 2.5/3G communication systems, the mobile device has become a window to the Internet. A natural interface to this mobile device is through speech. To address this need, a new European Telecommunications Standards Institute (ETSI) standard front-end has evolved for Distributed Speech Recognition (DSR). The goal of the ETSI DSR front-end i...
متن کاملSpeaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation
A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...
متن کاملA Low-resource, Miniature of the Etsi Distributed Speech R
The purpose of this work is to demonstrate that distributed speech recognition front-ends can be deployed in environments which providefor very little power and CPU resources, with possibly no degradation of speech recognition quality when compared to standard floatingpoint implementations. The ETSI distributed speech recognition front-end standard is implemented on an ultra low-power miniature...
متن کاملA low-resource, miniature implementation of the ETSI distributed speech recognition front-end
The purpose of this work is to demonstrate that distributed speech recognition front-ends can be deployed in environments which provide for very little power and CPU resources, with possibly no degradation of speech recognition quality when compared to standard floatingpoint implementations. The ETSI distributed speech recognition front-end standard is implemented on an ultra low-power miniatur...
متن کامل