IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Speech Disorders Recognition using Speech Analysis

Speech Disorders Recognition using Speech Analysis
View Sample PDF
Author(s): Khaled Necibi (University of Annaba, Algeria), Halima Bahi (University of Annaba, Algeria)and Toufik Sari (University of Annaba, Algeria)
Copyright: 2014
Pages: 14
Source title: Assistive Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-4422-9.ch024

Purchase

View Speech Disorders Recognition using Speech Analysis on the publisher's website for pricing and purchasing information.

Abstract

Speech disorders are human disabilities widely present in young population but also adults may suffer from such disorders after some physical problems. In this context, the detection and further the correction of such disabilities may be handled by Automatic Speech Recognition (ASR) technology. The first works on the speech disorders detection began early in the 70s and seem to follow the same evolution as those on the ASR. Indeed, these early works were more based on the signal processing techniques. Progressively, systems dealing with speech disorders incorporate more ideas from ASR technology. Particularly, Hidden Markov Models, the state-of-the-art approaches in ASR systems, are used. This chapter reviews systems that use ASR techniques to evaluate pronunciation of people who suffer from speech or voice impairments. The authors investigate the existing systems and present the main innovation and some of the available resources.

Related Content

Timothy Gifford. © 2023. 23 pages.
Sandy White Watson. © 2023. 18 pages.
Elaine Wilson, Sarah Chesney. © 2023. 32 pages.
Michael Finetti, Nicole Luongo. © 2023. 30 pages.
Anurag Vijay Agrawal, R. Pitchai, C. Senthamaraikannan, N. Alangudi Balaji, S. Sajithra, Sampath Boopathi. © 2023. 23 pages.
Keri A. Sullivan. © 2023. 13 pages.
Nicole L. Lambright. © 2023. 16 pages.
Body Bottom