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On the Issue of Speaker's Identification in Communication Networks and Terminal Equipment of Onboard System

机译:车载系统通信网络和终端设备中的说话人识别问题

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The work is dedicated to the issue of speech messages quality providing in communication networks, in particular, to study the influence of the state of functional systems of the speaker on the accuracy of his speech identification. The study allowed drawing a conclusion on quite clearly formalized correspondence between changes in speech signal parameters and disease groups that define them. Such formalization can be used to increase the identification reliability level of speech sources, and for timely and rapid diagnosis of a certain set of diseases, including their early development stage. Adequate identification of speech messages sources belongs to a common task group of ensuring effective and safe operation of automated control systems as well as access control systems. The second group of tasks, in some cases, may be associated with the first one and is caused by the need of personnel health state monitoring implementing management functions of important and challenging complex systems and processes. Also, the detection of several diseases signs at their early stages is very important task to ensure the implementation of research and production programs made by members of various expeditions teams, in particular, the crews working on board space stations. As a rule, the correspondent decision - making is usually based on the correlation analysis of speech signals, as well as on the evaluation of phonogram statistical parameters. The paper proposes and justifies the algorithm for speech source identification, in condition of a set of endogenous and exogenous factor presence, affecting its informative parameters.
机译:这项工作致力于解决通信网络中提供的语音消息质量问题,尤其是研究说话者功能系统的状态对其语音识别准确性的影响。这项研究可以得出结论,即语音信号参数的变化与定义它们的疾病组之间的对应关系非常明确。这种形式化可用于提高语音来源的识别可靠性水平,并用于及时,快速地诊断某些疾病,包括其早期发展阶段。语音消息源的充分标识属于确保自动控制系统和访问控制系统有效且安全运行的常见任务组。在某些情况下,第二组任务可能与第一组任务相关,这是由于需要人员健康状态监视来执行重要且具有挑战性的复杂系统和过程的管理功能而引起的。同样,在早期发现几种疾病的征兆也是一项非常重要的任务,以确保执行由各个探险队的成员,特别是在空间站上工作的机组人员制定的研究和生产计划。通常,相应的决策通常基于语音信号的相关性分析以及对录音统计参数的评估。提出并证明了在存在一组内源性和外源性因素影响语音信息参数的情况下,语音源识别算法的合理性。

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