Speaker verification: Minimizing the channel effects using autoassociative neural network models

被引：0
|
作者：
Kishore, SP [1 ]
Yegnanarayana, B [1 ]
机构：
[1] Indian Inst Technol, Dept Comp Sci & Engn, Madras 600036, Tamil Nadu, India
来源：
2000 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS, VOLS I-VI | 2000年
关键词：
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
The characteristics of telephone channel and handset have significant effect on the performance of speaker verification systems. The channel/handset mismatch between the training and testing data degrades the performance of speaker verification systems. In this paper, we show that the Autoassociative Neural Network (AANN) models can be used to minimize the effects of channel characteristics on the performance of text-independent speaker verification system. This paper also compares two approaches to represent the background model for AANN based speaker verification system.
引用
收藏
页码：1101 / 1104
页数：4
相关论文
共 50 条
  • [31] Tool Wear Monitoring during Milling Using an Autoassociative Neural Network
    Oh, Dae Jin
    Sim, Beom Sik
    Lee, Wonkyun
    TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS A, 2021, 45 (04) : 285 - 291
  • [32] Supervized Mixture of PLDA Models for Cross-Channel Speaker Verification
    Simonchik, Konstantin
    Pekhovsky, Timur
    Shulipa, Andrey
    Afanasyev, Anton
    13TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2012 (INTERSPEECH 2012), VOLS 1-3, 2012, : 1682 - 1685
  • [33] Speaker verification using heterogeneous neural network architecture with linear correlation speech activity detection
    Tashan, Tariq
    Allen, Tony
    Nolle, Lars
    EXPERT SYSTEMS, 2014, 31 (05) : 437 - 447
  • [34] Text-dependent speaker verification using genetic algorithm and competitive learning neural network
    Cho, Seongwon
    Kim, Jaemin
    Kim, Daehwan
    Kang, Jiwoon
    Lee, Jinhyung
    Kim, Hunki
    Kim, Seokho
    Oh, Dusik
    Jeon, Seoungseon
    Chung, Sun-Tae
    PROCEEDINGS OF THE FOURTH IASTED INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, PATTERN RECOGNITION, AND APPLICATIONS, 2007, : 293 - +
  • [35] Speaker verification using adapted Gaussian mixture models
    Reynolds, DA
    Quatieri, TF
    Dunn, RB
    DIGITAL SIGNAL PROCESSING, 2000, 10 (1-3) : 19 - 41
  • [36] DEEP NEURAL NETWORK-BASED SPEAKER EMBEDDINGS FOR END-TO-END SPEAKER VERIFICATION
    Snyder, David
    Ghahremani, Pegah
    Povey, Daniel
    Garcia-Romero, Daniel
    Carmiel, Yishay
    Khudanpur, Sanjeev
    2016 IEEE WORKSHOP ON SPOKEN LANGUAGE TECHNOLOGY (SLT 2016), 2016, : 165 - 170
  • [37] A Deep Neural Network Speaker Verification System Targeting Microphone Speech
    Lei, Yun
    Ferrer, Luciana
    McLaren, Mitchell
    Scheffer, Nicolas
    15TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2014), VOLS 1-4, 2014, : 681 - 685
  • [38] Neural Network based Speaker Classification and Verification Systems with Enhanced Features
    Ge, Zhenhao
    Iyer, Ananth N.
    Cheluvaraja, Srinath
    Sundaram, Ram
    Ganapathiraju, Aravind
    PROCEEDINGS OF THE 2017 INTELLIGENT SYSTEMS CONFERENCE (INTELLISYS), 2017, : 1089 - 1094
  • [39] Total Variability Layer in Deep Neural Network Embeddings for Speaker Verification
    Travadi, Ruchir
    Narayanan, Shrikanth
    IEEE SIGNAL PROCESSING LETTERS, 2019, 26 (06) : 893 - 897
  • [40] STATISTICAL PYRAMID DENSE TIME DELAY NEURAL NETWORK FOR SPEAKER VERIFICATION
    Wan, Zi-Kai
    Ren, Qing-Hua
    Qin, You-Cai
    Mao, Qi-Rong
    2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2022, : 7532 - 7536
12345