Voice Recognition and Voice Comparison using Machine Learning Techniques: A Survey

被引:0
|
作者
Tandel, Nishtha H. [1 ]
Prajapati, Harshadkumar B. [1 ]
Dabhi, Vipul K. [1 ]
机构
[1] Dharmsinh Desai Univ, Dept Informat Technol, Nadiad, India
关键词
voice comparison; speaker recognition; deep learning; Siamese NN; SPEAKER IDENTIFICATION;
D O I
10.1109/icaccs48705.2020.9074184
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Voice comparison is a variant of speaker recognition or voice recognition. Voice comparison plays a significant role in the forensic science field and security systems. Precise voice comparison is a challenging problem. Traditionally, different classification and comparison models were used by the researchers to solve the speaker recognition and the voice comparison, respectively but deep learning is gaining popularity because of its strength in accuracy when trained with large amounts of data. This paper focuses on an elaborated literature survey on both traditional and deep learning-based methods of speaker recognition and voice comparison. This paper also discusses publicly available datasets that are used for speaker recognition and voice comparison by researchers. This concise paper would provide substantial input to beginners and researchers for understanding the domain of voice recognition and voice comparison.
引用
收藏
页码:459 / 465
页数:7
相关论文
共 50 条
  • [41] Laughing Voice Recognition Using Periodic Waveforms and Voice-likeness Features - Toward Advanced Human-machine -
    Sakano, Taisuke
    Kigawa, Takahiro
    Sugimoto, Masanori
    Kusunoki, Fusako
    Inagaki, Shigenori
    Mizoguchi, Hiroshi
    2016 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO), 2016, : 964 - 969
  • [42] The accuracy of an Online Sequential Extreme Learning Machine in detecting voice pathology using the Malaysian Voice Pathology Database
    Nur Ain Nabila Za’im
    Fahad Taha AL-Dhief
    Mawaddah Azman
    Majid Razaq Mohamed Alsemawi
    Nurul Mu′azzah Abdul Latiff
    Marina Mat Baki
    Journal of Otolaryngology - Head & Neck Surgery, 52
  • [43] The accuracy of an Online Sequential Extreme Learning Machine in detecting voice pathology using the Malaysian Voice Pathology Database
    Za'im, Nur Ain Nabila
    AL-Dhief, Fahad Taha
    Azman, Mawaddah
    Alsemawi, Majid Razaq Mohamed
    Abdul Latiff, Nurul Mu'azzah
    Baki, Marina Mat
    JOURNAL OF OTOLARYNGOLOGY-HEAD & NECK SURGERY, 2023, 52 (01)
  • [44] Validation of Voice Recognition in Various Google Voice Languages using Voice Recognition Module V3 Based on Microcontroller
    Khotimah, Khusnul
    Santoso, Agus Budi
    Ma'arif, Miftahul
    Azhiimah, Alfiantin Noor
    Suprianto, Bambang
    Sumbawati, Meini Sondang
    Rijanto, Tri
    2020 THIRD INTERNATIONAL CONFERENCE ON VOCATIONAL EDUCATION AND ELECTRICAL ENGINEERING (ICVEE): STRENGTHENING THE FRAMEWORK OF SOCIETY 5.0 THROUGH INNOVATIONS IN EDUCATION, ELECTRICAL, ENGINEERING AND INFORMATICS ENGINEERING, 2020,
  • [45] Using PCA algorithm in voice recognition
    Gorgunoglu, S. (sgorgunoglu@karabuk.edu.tr), 1600, Sila Science, University Mah Mekan Sok, No 24, Trabzon, Turkey (30):
  • [46] Voice recognition using neural networks
    Venayagamoorthy, Ganesh K.
    Moonasar, Viresh
    Sandrasegaran, Kumbes
    Proceedings of the South African Symposium on Communications and Signal Processing, COMSIG, 1998, : 29 - 32
  • [47] COMPARISON OF MODULATION TECHNIQUES FOR QUANTIZED VOICE COMMUNICATIONS
    DUFFIELD, TL
    IEEE TRANSACTIONS ON COMMUNICATION TECHNOLOGY, 1970, CO18 (05): : 543 - &
  • [48] A Comparison of Human and Machine-Generated Voice
    Abdulrahman, Amal
    Richards, Deborah
    Bilgin, Ayse Aysin
    25TH ACM SYMPOSIUM ON VIRTUAL REALITY SOFTWARE AND TECHNOLOGY (VRST 2019), 2019,
  • [49] Voice-Activated Smart Home Controller Using Machine Learning
    Filipe, Leandro
    Peres, Ricardo Silva
    Tavares, Rui Manuel
    IEEE ACCESS, 2021, 9 : 66852 - 66863
  • [50] Characterization between Child and Adult voice using Machine Learning Algorithm
    Aggarwal, Gaurav
    Singh, Latika
    2015 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION & AUTOMATION (ICCCA), 2015, : 246 - 250