SPEECH RECOGNITION OPEN SOURCE TOOLS FOR THE SEMANTIC IDENTIFICATION OF THE SENTENCE

被引:0
|
作者
Shanmugapriya, R. [1 ]
RajaMohammed, S. [1 ]
机构
[1] Kalaignar Karunanidhi Inst Technol, Dept Comp Sci & Engn, Coimbatore, Tamil Nadu, India
关键词
Speech Recognition; Speech to text; learning Disabilities; Natural Language Processing; knowledge;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In the NLP world the recognizing speech as in the voice recognition and also allowing voice to serve as the "main interface between the human and the computer. This paper mainly focuses on the tools that are used to deliver how current speech recognition technology facilitates the learning part of the students, and also in what way the technology will be help to developing the advance learning system for future. The tools like speech to text conversion are to be discussed in this paper and also focused some attributes for the semantic identification. Although speech recognition has a potential benefit for students with physical disabilities and harsh learning disabilities, these are the technology in which it has been implemented inconsistently in the classroom above the years. By means of this the knowledge continues to develop, on the other hand, various issues are being addressed.
引用
收藏
页数:3
相关论文
共 50 条
  • [21] Open Source German Distant Speech Recognition: Corpus and Acoustic Model
    Radeck-Arneth, Stephan
    Milde, Benjamin
    Lange, Arvid
    Gouvea, Evandro
    Radomski, Stefan
    Muehlhaeuser, Max
    Biemann, Chris
    [J]. TEXT, SPEECH, AND DIALOGUE (TSD 2015), 2015, 9302 : 480 - 488
  • [22] AISHELL-1: AN OPEN-SOURCE MANDARIN SPEECH CORPUS AND A SPEECH RECOGNITION BASELINE
    Bu, Hui
    Du, Jiayu
    Na, Xingyu
    Wu, Bengu
    Zheng, Hao
    [J]. 2017 20TH CONFERENCE OF THE ORIENTAL CHAPTER OF THE INTERNATIONAL COORDINATING COMMITTEE ON SPEECH DATABASES AND SPEECH I/O SYSTEMS AND ASSESSMENT (O-COCOSDA), 2017, : 58 - 62
  • [23] Enhancing multilingual speech recognition in air traffic control by sentence-level language identification
    Fan, Peng
    Guo, Dongyue
    Zhang, Jianwei
    Yang, Bo
    Lin, Yi
    [J]. APPLIED ACOUSTICS, 2024, 224
  • [24] IMAGERY EFFECTS AND SEMANTIC SIMILARITY IN SENTENCE RECOGNITION MEMORY
    SLACK, JM
    [J]. MEMORY & COGNITION, 1983, 11 (06) : 631 - 640
  • [25] Semantic Role Labeling of Speech Transcripts Without Sentence Boundaries
    Shrestha, Niraj
    Moens, Marie-Francine
    [J]. TEXT, SPEECH, AND DIALOGUE (TSD 2018), 2018, 11107 : 379 - 387
  • [26] SYNTACTIC AND SEMANTIC POSTPROCESSING FOR SPEECH RECOGNITION
    KRALLMANN, H
    MARZI, R
    [J]. DECISION SUPPORT SYSTEMS, 1991, 7 (03) : 253 - 261
  • [27] Open-source toolkit for end-to-end Korean speech recognition
    Kim, Soohwan
    Bae, Seyoung
    Won, Cheolhwang
    [J]. SOFTWARE IMPACTS, 2021, 7
  • [28] Implementation of a Radiology Speech Recognition System for Estonian using Open Source Software
    Alumae, Tanel
    Paats, Andrus
    Fridolin, Ivo
    Meister, Einar
    [J]. 18TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2017), VOLS 1-6: SITUATED INTERACTION, 2017, : 2168 - 2172
  • [29] SPEED: Open-source framework to accelerate speech recognition on embedded GPUs
    Intesa, Leonardo
    Jafri, Syed M. A. H.
    Hemani, Ahmed
    [J]. 2017 EUROMICRO CONFERENCE ON DIGITAL SYSTEM DESIGN (DSD), 2017, : 94 - 101
  • [30] Towards an Open-Source Dutch Speech Recognition System for the Healthcare Domain
    Tejedor-Garcia, Cristian
    van der Molen, Berrie
    van den Heuvel, Henk
    van Hessen, Arjan
    Pieters, Toine
    [J]. LREC 2022: THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2022, : 1032 - 1039