An automatic speech recognition system in Indian and foreign languages: A state-of-the-art review analysis

被引:0
|
作者
Gupta A. [1 ]
Kumar R. [1 ]
Kumar Y. [2 ]
机构
[1] Department of Computer Science and Engineering, Chandigarh University, Punjab, Mohali
[2] Department of Computer Science and Engineering, Pandit Deendayal Energy University, Gujarat, Gandhinagar
关键词
ASRS; CMU Sphinx; deep learning; HMM toolkit; Kaldi toolkit;
D O I
10.3233/IDT-220228
中图分类号
学科分类号
摘要
Speech Recognition is one of the prominent research topics in the field of Natural Language Processing (NLP). The Speech Recognition technique removes the barriers and makes the system ease for inter-communication between human beings and devices. The aim of this study is to analyze the Automatic Speech Recognition System (ASRS) proposed by different researchers using Machine learning and Deep Learning techniques. In this work, Indian and foreign languages speech recognition systems like Hindi, Marathi, Malayalam, Urdu, Sanskrit, Nepali, Kannada, Chinese, Japanese, Arabic, Italian, Turkish, French, and German are considered. An integrated framework is presented and elaborated with recent advancement. The various platform like Hidden Markov Model Toolkit (HMM Toolkit), CMU Sphinx, Kaldi toolkit are explained which is used for building the speech recognition model. Further, some applications are elaborated which depict the uses of ASRS. © 2023 - IOS Press. All rights reserved.
引用
收藏
页码:505 / 526
页数:21
相关论文
共 50 条
  • [1] Automatic Speech Recognition System for Tonal Languages: State-of-the-Art Survey
    Kaur, Jaspreet
    Singh, Amitoj
    Kadyan, Virender
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2021, 28 (03) : 1039 - 1068
  • [2] Automatic Speech Recognition System for Tonal Languages: State-of-the-Art Survey
    Jaspreet Kaur
    Amitoj Singh
    Virender Kadyan
    Archives of Computational Methods in Engineering, 2021, 28 : 1039 - 1068
  • [3] State-of-the-Art Review on Recent Trends in Automatic Speech Recognition
    Kandji, Abdou Karim
    Ba, Cheikh
    Ndiaye, Samba
    EMERGING TECHNOLOGIES FOR DEVELOPING COUNTRIES, AFRICATEK 2023, 2024, 520 : 185 - 203
  • [4] THE STATE-OF-THE-ART IN SPEECH RECOGNITION
    BISIANI, R
    TRENDS IN NEUROSCIENCES, 1985, 8 (01) : 9 - 11
  • [5] Analysis and Review of State-of-the-Art Automatic Parking Assist System
    Song, Yuyu
    Liao, Chenglin
    2016 IEEE INTERNATIONAL CONFERENCE ON VEHICULAR ELECTRONICS AND SAFETY (ICVES), 2016, : 61 - 66
  • [6] STATE-OF-THE-ART IN CONTINUOUS SPEECH RECOGNITION
    MAKHOUL, J
    SCHWARTZ, R
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1995, 92 (22) : 9956 - 9963
  • [7] Automatic License Plate Recognition (ALPR): A State-of-the-Art Review
    Du, Shan
    Ibrahim, Mahmoud
    Shehata, Mohamed
    Badawy, Wael
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2013, 23 (02) : 322 - 336
  • [8] Audio-Visual Automatic Speech Recognition and Related Bimodal Speech Technologies: A Review of the State-of-the-Art and Open Problems
    Potamianos, Gerasimos
    2009 IEEE WORKSHOP ON AUTOMATIC SPEECH RECOGNITION & UNDERSTANDING (ASRU 2009), 2009, : 22 - 22
  • [9] Performance vs. hardware requirements in state-of-the-art automatic speech recognition
    Georgescu, Alexandru-Lucian
    Pappalardo, Alessandro
    Cucu, Horia
    Blott, Michaela
    EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING, 2021, 2021 (01)
  • [10] Performance vs. hardware requirements in state-of-the-art automatic speech recognition
    Alexandru-Lucian Georgescu
    Alessandro Pappalardo
    Horia Cucu
    Michaela Blott
    EURASIP Journal on Audio, Speech, and Music Processing, 2021