Review of various stages in speaker recognition system, performance measures and recognition toolkits

被引:14
|
作者
Pawar, Rupali V. [1 ]
Jalnekar, Rajesh M. [2 ]
Chitode, Janardan S. [3 ]
机构
[1] Sinhgad Coll Engn, Pune, Maharashtra, India
[2] Vishwakarma Inst Technol, Pune, Maharashtra, India
[3] Vishwakarma Inst Technol, Dept E&TC, Pune, Maharashtra, India
关键词
Pre-processing; Framing; Feature extraction; Generative and discriminative model; Toolkits; Performance measures; Receiver operating characteristics (ROC); Decision error trade off (DET); Equal error rate (EER); SPEECH RECOGNITION; IDENTIFICATION;
D O I
10.1007/s10470-017-1069-1
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Speaker Recognition is a vital application of speech processing. Speaker Recognition performs a task of authenticating or recognizing a speaker based on the unique features captured which characterize the speaker. Characteristics or features which are unique to an individual such as fundamental frequency, speaking style, pitch, and duration are used as distinguishing components of the human speech signal. Exploring these characteristics for various applications with an attempt to implement a robust speaker recognition system has been the impetus behind the research in this domain. This paper makes an attempt to present the available Feature Extraction and Recognition techniques with their merits and demerits. It also discusses the pre-emphasis stage of the speaker recognition system. The standard databases available for speaker recognition along with the criterion for their selection are also reviewed. The paper presents an overview of various toolkits and performance parameters of Automatic Speaker Recognition System.
引用
收藏
页码:247 / 257
页数:11
相关论文
共 50 条
  • [21] Source and System Features for Text Independent Speaker Recognition Using GMM Speaker Models
    Revathi, A.
    Venkataramani, Y.
    RECENT TRENDS IN NETWORKS AND COMMUNICATIONS, 2010, 90 : 21 - +
  • [22] Speaker Authentication System Based on Voice Biometrics and Speech Recognition
    Dovydaitis, Laurynas
    Rasymas, Tomas
    Rudzionis, Vytautas
    BUSINESS INFORMATION SYSTEMS WORKSHOPS, BIS 2016, 2017, 263 : 79 - 84
  • [23] New Technique to use the GMM in Speaker Recognition System (SRS)
    Cherifa, Snani
    Messaoud, Ramdani
    2013 INTERNATIONAL CONFERENCE ON COMPUTER APPLICATIONS TECHNOLOGY (ICCAT), 2013,
  • [24] DWT-MFCC Method for Speaker Recognition System with Noise
    Amelia, Fetty
    Gunawan, Dadang
    2019 7TH INTERNATIONAL CONFERENCE ON SMART COMPUTING & COMMUNICATIONS (ICSCC), 2019, : 310 - 314
  • [25] Multidimensional Speaker Information Recognition based on Proposed Baseline System
    Li, Shan
    Xu, Longting
    Yang, Zhen
    2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC), 2017, : 1776 - 1780
  • [26] ASSESSING THE SPEAKER RECOGNITION PERFORMANCE OF NAIVE LISTENERS USING MECHANICAL TURK
    Shen, Wade
    Campbell, Joseph
    Straub, Derek
    Schwartz, Reva
    2011 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2011, : 5916 - 5919
  • [27] An automatic speech recognition system with speaker-independent identification support
    Caranica, Alexandru
    Burileanu, Corneliu
    ADVANCED TOPICS IN OPTOELECTRONICS, MICROELECTRONICS, AND NANOTECHNOLOGIES VII, 2015, 9258
  • [28] Phone-based Cepstral Polynomial SVM System for Speaker Recognition
    Kajarekar, Sachin S.
    INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5, 2008, : 845 - 848
  • [29] Assessment of a Speaker Recognition System Based on an Auditory Model and Neural Nets
    Martinez-Rams, Ernesto A.
    Garceran-Hernandez, Vicente
    BIOINSPIRED APPLICATIONS IN ARTIFICIAL AND NATURAL COMPUTATION, PT II, 2009, 5602 : 488 - +
  • [30] VQ Based Comparative Analysis of MFCC and LPC Speaker Recognition System
    Naveed, Iqra
    Saher, Farwa
    Ali, Muhammad Nadeem
    Farooq, Muhammad Sajid
    Hasan, Taimoor
    Iftikhar, Aqsa
    4TH INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING (IC)2, 2021, : 165 - 170