Comparative Analysis of Classifiers for Automatic Language Recognition in Spontaneous Speech

被引：1
|
作者：
Simonchik, Konstantin [1 ,2 ]
Novoselov, Sergey [1 ,2 ]
Lavrentyeva, Galina [1 ,2 ]
机构：
[1] ITMO Univ, St Petersburg, Russia
[2] Speech Technol Ctr, Krasutskogo St 4, St Petersburg 196084, Russia
来源：
SPEECH AND COMPUTER | 2016年 / 9811卷
关键词：
Language recognition; i-vectors; SVM; LDA; Naive bayes;
D O I：
10.1007/978-3-319-43958-7_20
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we consider a language identification system based on the state-of-the-art i-vector method. Paper presents a comparative analysis of different methods for the classification in the i-vector space to determine the most efficient for this task. Experimental results show the reliability of the method based on linear discriminant analysis and naive Bayes classifier which is sufficient for usage in practical applications.
引用
收藏
页码：174 / 181
页数：8
相关论文
共 50 条
  • [31] On the Design of an Automatic Speech Recognition System for Romanian Language
    Caranica, Alexandru
    Cucu, Horia
    Buzo, Audi
    Burileanu, Corneliu
    CONTROL ENGINEERING AND APPLIED INFORMATICS, 2016, 18 (02): : 65 - 76
  • [32] Effect of Language Resources on Automatic Speech Recognition for Amharic
    Tachbelie, Martha Yifiru
    Abate, Solomon Teferra
    PROCEEDINGS OF THE 2015 12TH IEEE AFRICON INTERNATIONAL CONFERENCE - GREEN INNOVATION FOR AFRICAN RENAISSANCE (AFRICON), 2015,
  • [33] JOINT LANGUAGE MODELS FOR AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING
    Bayer, Ali Orkan
    Riccardi, Giuseppe
    2012 IEEE WORKSHOP ON SPOKEN LANGUAGE TECHNOLOGY (SLT 2012), 2012, : 199 - 203
  • [34] MACHINE RECOGNITION OF HUMAN LANGUAGE .I. AUTOMATIC SPEECH RECOGNITION
    LINDGREN, N
    IEEE SPECTRUM, 1965, 2 (03) : 114 - +
  • [35] Comparative Analysis of Various Classifiers for Gesture Recognition
    Gupta, Rahul
    Rana, Sarthak
    Gupta, Swapnil
    Pandey, Kavita
    Dabas, Chetna
    INTELLIGENT COMPUTING TECHNIQUES FOR SMART ENERGY SYSTEMS, 2020, 607 : 85 - 94
  • [36] Acoustic Analysis for Automatic Speech Recognition
    O'Shaughnessy, Douglas
    PROCEEDINGS OF THE IEEE, 2013, 101 (05) : 1038 - 1053
  • [37] Vocabulary Size Influences Spontaneous Speech in Native Language Users: Validating the Use of Automatic Speech Recognition in Individual Differences Research
    Jongman, Suzanne R.
    Khoe, Yung Han
    Hintz, Florian
    LANGUAGE AND SPEECH, 2021, 64 (01) : 35 - 51
  • [38] Prosody for Mandarin Speech Recognition: a Comparative Study of Read and Spontaneous Speech
    Yeung, Yu Ting
    Qian, Yao
    Lee, Tan
    Soong, Frank K.
    INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5, 2008, : 1133 - +
  • [39] A Comparative Analysis of Classifiers in the Recognition of Packed Executables
    Assis, Cecilia R. O.
    Miani, Rodrigo S.
    Carneiro, Murillo G.
    Park, Kil J. B.
    2019 IEEE 31ST INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2019), 2019, : 1356 - 1360
  • [40] A Comparative Analysis of Automatic Speech Recognition Errors in Small Group Classroom Discourse
    Cao, Jie
    Ganesh, Ananya
    Cai, Jon
    Southwell, Rosy
    Perkoff, E. Margaret
    Regan, Michael
    Kann, Katharina
    Martin, James H.
    Palmer, Martha
    D'Mello, Sidney
    2023 PROCEEDINGS OF THE 31ST ACM CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION, UMAP 2023, 2023, : 250 - 262
12345