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

作　　者：Rand Kouatly Talha Ali Khan 

机构地区：[1]Faculty of Tech and Software Engineering,University of Europe for Applied Sciences,Potsdam 14469,Germany

出　　处：《Tsinghua Science and Technology》2024年第2期447-456,共10页清华大学学报（自然科学版（英文版）

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 procedures.Shared memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR algorithm.The 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.

关 键 词：Automatic Speaker Recognition(ASR) Gaussian Mixture Model(GMM) shared memory parallel programming PThreads OPENMP 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TN761[自动化与计算机技术—控制科学与工程]