Performance of Text-Independent Automatic Speaker Recognition on a Multicore System

作     者：Rand Kouatly Talha Ali Khan 

作者机构：Faculty of Tech and Software EngineeringUniversity of Europe for Applied SciencesPotsdam 14469Germany 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2024年第29卷第2期

页      面：447-456页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 080902[工学-电路与系统] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Automatic Speaker Recognition(ASR) Gaussian Mixture Model(GMM) shared memory parallel programming PThreads OpenMP 

摘      要：This paper studies a high-speed text-independent Automatic Speaker Recognition(ASR)algorithm based on a multicore system s Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of the feature s extraction and aggregation methods during training and testing *** memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR *** experimental results show speed-up improvements of around 3.2 on a personal laptop with Intel i5-6300HQ(2.3 GHz,four cores without hyper-threading,and 8 GB of RAM).In addition,a remarkable 100%speaker recognition accuracy is achieved.