Audio-Visual Automatic Speech Recognition Towards Education for Disabilities.
Education is a fundamental right that enriches everyone's life. However, physically challenged people often debar from the general and advanced education system. Audio-Visual Automatic Speech Recognition (AV-ASR) based system is useful to improve the education of physically challenged people by prov...
| Publicado en: | Journal of Autism & Developmental Disorders Vol. 53; no. 9; pp. 3581 - 3595 |
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| Autores principales: | , , , |
| Formato: | algorithm equations & formulas review tables/charts Journal Article |
| Publicado: |
Springer Nature
Sep2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=170899336&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 170899336 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01623257 AUT jtl: Journal of Autism & Developmental Disorders issn: 01623257 maglogo: N pubinfo: dt: Sep2023 vid: 53 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 170899336 157931499 170899336 170899336 10.1007/s10803-022-05654-4 170899336 ppf: 3581 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Audio-Visual Automatic Speech Recognition Towards Education for Disabilities. aug: au: Debnath, Saswati Roy, Pinki Namasudra, Suyel Crespo, Ruben Gonzalez affil: Department of Computer Science and Engineering, Alliance University, Bangalore, Karnataka, India sug: subj: Audiovisuals Automation Voice Recognition Systems Persons with Disabilities Education Learning Methods Quality Improvement Visual Perception Speech Perception ab: Education is a fundamental right that enriches everyone's life. However, physically challenged people often debar from the general and advanced education system. Audio-Visual Automatic Speech Recognition (AV-ASR) based system is useful to improve the education of physically challenged people by providing hands-free computing. They can communicate to the learning system through AV-ASR. However, it is challenging to trace the lip correctly for visual modality. Thus, this paper addresses the appearance-based visual feature along with the co-occurrence statistical measure for visual speech recognition. Local Binary Pattern-Three Orthogonal Planes (LBP-TOP) and Grey-Level Co-occurrence Matrix (GLCM) is proposed for visual speech information. The experimental results show that the proposed system achieves 76.60 % accuracy for visual speech and 96.00 % accuracy for audio speech recognition. pubtype: Academic Journal doctype: algorithm equations & formulas review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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