AUTOMATIC SPEECH RECOGNITION TECHNOLOGY AND THE SUPPORT OF STUDENTS WITH SPECIAL NEEDS

被引:0
作者
Martinik, Ivo [1 ]
机构
[1] VSB Tech Univ Ostrava, Fac Econ, Ostrava, Czech Republic
来源
EFFICIENCY AND RESPONSIBILITY IN EDUCATION 2013 | 2013年
关键词
Rich-media; Automatic Speech Recognition; MERLINGO; students with special needs; SWOT analysis;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Rich-media describes a broad range of digital interactive media that is increasingly used in the Internet and also for the support of education, where the complex rich-media visualization of the educational process becomes the necessity for the overall transfer of information from teacher to students. Rich-media technologies are used for the support of students with special needs mainly at the development of 'barrier-free' information access to records of presentations which are adapted to needs especially in students of locomotive, visual and aural disability. SWOT analysis of these services determined also future development of MERLINGO (MEdia-rich Repository of LearnING Objects) project and the MIN-MAX strategy of its progress was chosen. Therefore, new objectives of the project involving support of students with special needs have been specified and implemented. The stated needs are focused on the area of the automatic recognition of teacher's speech in real time and its transcription into a text form in order to support students with aural disability at lectures and practical training, followed by automation of sub-titling of video-records made by rich-media technologies and browsing in them in real time according to entered key words while using the programming system NovaVoice and Automatic Speech Recognition technology.
引用
收藏
页码:397 / 404
页数:8
相关论文
共 50 条
[41]   Refining maritime Automatic Speech Recognition by leveraging synthetic speech [J].
Martius, Christoph ;
Nakilcioglu, Emin Cagatay ;
Reimann, Maximilian ;
John, Ole .
MARITIME TRANSPORT RESEARCH, 2024, 7
[42]   Real and synthetic Punjabi speech datasets for automatic speech recognition [J].
Singh, Satwinder ;
Hou, Feng ;
Wang, Ruili .
DATA IN BRIEF, 2024, 52
[43]   Chhattisgarhi speech corpus for research and development in automatic speech recognition [J].
Londhe, Narendra D. ;
Kshirsagar, Ghanahshyam B. .
INTERNATIONAL JOURNAL OF SPEECH TECHNOLOGY, 2018, 21 (02) :193-210
[44]   Autonomous measurement of speech intelligibility utilizing automatic speech recognition [J].
Meyer, Bernd T. ;
Kollmeier, Birger ;
Ooster, Jasper .
16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5, 2015, :2982-2986
[45]   KsponSpeech: Korean Spontaneous Speech Corpus for Automatic Speech Recognition [J].
Bang, Jeong-Uk ;
Yun, Seung ;
Kim, Seung-Hi ;
Choi, Mu-Yeol ;
Lee, Min-Kyu ;
Kim, Yeo-Jeong ;
Kim, Dong-Hyun ;
Park, Jun ;
Lee, Young-Jik ;
Kim, Sang-Hun .
APPLIED SCIENCES-BASEL, 2020, 10 (19) :1-17
[46]   Fine-Tuning Automatic Speech Recognition for People with Parkinson's: An Effective Strategy for Enhancing Speech Technology Accessibility [J].
Zheng, Xiuwen ;
Phukon, Bornali ;
Hasegawa-Johnson, Mark .
INTERSPEECH 2024, 2024, :2485-2489
[47]   A huggable communication medium can provide sustained listening support for special needs students in a classroom [J].
Nakanishi, Junya ;
Sumioka, Hidenobu ;
Ishiguro, Hiroshi .
COMPUTERS IN HUMAN BEHAVIOR, 2019, 93 :106-113
[48]   Support and Perceptions of Teachers Working with Students with Special Needs during the COVID-19 Pandemic [J].
Donnelly, Hayoung Kim ;
Solberg, V. Scott H. ;
Shavers, Efe I. ;
Howard, Kimberly A. S. ;
Ismail, Bushra ;
Nieves, Hector .
EDUCATION SCIENCES, 2022, 12 (08)
[49]   Gender Independent Bangla Automatic Speech Recognition [J].
Hassan, Foyzul ;
Kotwal, Mohammed Rokibul Alam ;
Khan, Mohammad Saiful Alam ;
Huda, Mohammad Nurul .
2012 INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV), 2012, :143-148
[50]   Croatian Large Vocabulary Automatic Speech Recognition [J].
Martincic-Ipsic, Sanda ;
Pobar, Miran ;
Ipsic, Ivo .
AUTOMATIKA, 2011, 52 (02) :147-157