TREN-SI: A DCOM-Based Speaker Identification Software

A. Kanak, Y. Bicil, M. U. Dogan, H. Palaz
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Abstract

Recognition engines are common tools for both speech and speaker recognition. With this respect, TREN-SI (Turkish recognition engine for speaker identification) is presented as a hidden Markov model-based (HMM-based), two-layered distributed speaker identification software. TREN-SI contains specialized modules that allow a full interoperable platform including a speaker recognizer, feature extractor and a performance monitoring module. TREN-SI has basically two layers: First layer is the central server that distributes the calls acquired from different people to the appropriate remote servers according to their current CPU load of the recognition process after some speech signal preprocessing and the second layer consists of the remote servers which performs the critical speaker recognition task. This component-based architecture enables TREN-SI applicable to distributed environments. TREN-SI is developed as a solution especially for physical or logical access control problems considering user authentication and authorization
基于dcom的说话人识别软件
识别引擎是语音和说话人识别的常用工具。在这方面,trenn - si(土耳其语识别引擎,用于说话人识别)是一种基于隐马尔可夫模型(HMM-based)的两层分布式说话人识别软件。trenn - si包含专门的模块,允许一个完整的可互操作平台,包括扬声器识别器,特征提取器和性能监控模块。trenn - si基本上有两层:第一层是中央服务器,经过一些语音信号预处理后,根据识别过程中不同人的呼叫分配给相应的远程服务器,第二层由远程服务器组成,执行关键的说话人识别任务。这种基于组件的体系结构使treni - si能够适用于分布式环境。trenn - si是专门为考虑用户身份验证和授权的物理或逻辑访问控制问题而开发的解决方案
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