SROC: A Speaker Recognition with Data Decision Level Fusion Method in Cloud Environment

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• 作者：Ning Jiang ; Meikang Qiu ; Wenyun Dai
• 关键词：Speaker recognition ; SROC ; D ; S evidence theory ; Data fusion ; Cloud computing
• 刊名：Journal of Signal Processing Systems
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：86
• 期：2-3
• 页码：123-133
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Signal,Image and Speech Processing; Circuits and Systems; Electrical Engineering; Image Processing and Computer Vision; Pattern Recognition; Computer Imaging, Vision, Pattern Recognition and Graphics;
• 出版者：Springer US
• ISSN：1939-8115
• 卷排序：86

文摘

Speaker recognition as one of biometrics techniques is to recognize speaker’s identity. A robust method for speaker recognition with high accuracy of recognition rate is the aim for all relevant researchers. With the rapid development of cloud computing, many complicated tasks in speaker recognition system, such as machine learning, data processing, and information recording, can be implemented in cloud. Meanwhile, speaker recognition can be used as a security and privacy service which are extremely important for the popularization of cloud computing. In this paper, we propose a data decision level fusion method for speaker recognition in cloud environment. After introducing the basic processing of speech recognition process and describing the composition of the speech recognition system based on Dempster-Shafer Evidence Theory of decision level data fusion method, we present a speaker recognition system of cloud computing (SROC) architecture. Through experimental evaluation, SROC can improve the recognition rate and accuracy greatly.