A review on speaker recognition: Technology and challenges. (March 2021)

• Record Type: Journal Article
• Authors: Mohd Hanifa, Rafizah; Isa, Khalid; Mohamad, Shamsul
• Is Part Of: Computers & electrical engineering. Volume 90(2021)
• Publication Date: 2021-03
• Subjects: Biometric -- Open system -- Speaker recognition -- Text-independent -- Feature extraction -- Classifier -- Machine learning -- Adversarial attack; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2021.107005
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Voice is a behavioral biometric that conveys information about a person's traits. Components of speaker recognition include enrolment and recognition. Adversarial attacks can fool machine learning into giving incorrect predictions. Research progress in speaker recognition in the last decade. Abstract: Voice is a behavioral biometric that conveys information related to a person's traits, such as the speaker's ethnicity, age, gender, and feeling. Speaker recognition deals with recognizing the identity of people based on their voice. Although researchers have been working on speaker recognition in the last eight decades, advancements in technology, such as the Internet of Things (IoT), smart devices, voice assistants, smart homes, and humanoids, have made its usage nowadays trendy. This paper provides a comprehensive review of the literature on speaker recognition. It discusses the advances made in the last decade, including the challenges in this area of research. This paper also highlights the system and structure of speaker recognition as well as its feature extraction and classifiers. The use of speaker recognition in applications is also presented. As recent studies showed the possibility of fooling machine learning into giving an incorrect prediction; thus, the adversarial attack is also discussed. The aim is to enhance researchers' understanding in the area of speaker recognition. Graphical abstract: Image, graphical abstract