eprintid: 4814
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/48/14
datestamp: 2023-11-09 16:16:31
lastmod: 2023-11-09 16:16:31
status_changed: 2023-11-09 15:59:33
type: conference_item
metadata_visibility: show
creators_name: Ali, Z.
creators_name: Muhammad, G.
creators_name: Alsulaiman, M.
creators_name: Elamvazuthi, I.
creators_name: Al-Mutib, K.
title: Automatic speech recognition for dysphonic patients by using oriented local features
ispublished: pub
keywords: Speech, Arabic digits; Automatic speech recognition; HMM; MFCC; Vocal folds, Speech recognition
note: cited By 0; Conference of 27th International Conference on Computer Applications in Industry and Engineering, CAINE 2014 ; Conference Date: 13 October 2014 Through 15 October 2014; Conference Code:109020
abstract: The number of patients with voice pathology has increased significantly in recent years. The disability or illness of a person should not deprive him from taking benefits of the technology advances that is changing the daily life. For example, modern day speech recognition technology should be capable to recognize a speech from a normal person as well as a person having dysphonic. In this paper, we propose a new speech feature to use in automatic speech recognition system of disordered speech. We compare the performance of this feature with the most widely used speech feature in speech recognition. The comparison is done using spoken words uttered by both normal and dysphonic patients. The obtained results with the proposed technique are good and comparable to the existing method. Copyright ISCA, CAINE 2014.
date: 2014
publisher: International Society of Computers and Their Applications (ISCA)
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84913598714&partnerID=40&md5=4d138ace7c38a0c467ceb5bbbf8fa9a8
full_text_status: none
publication: 27th International Conference on Computer Applications in Industry and Engineering, CAINE 2014
pagerange: 269-274
refereed: TRUE
isbn: 9781880843970
citation:   Ali, Z. and Muhammad, G. and Alsulaiman, M. and Elamvazuthi, I. and Al-Mutib, K.  (2014) Automatic speech recognition for dysphonic patients by using oriented local features.  In: UNSPECIFIED.