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Articulation Error Detection Techniques and Tools:

by Khushbu Bansal, Shailendra Singh, Dharam Vir, Swati Sharma
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 10
Year of Publication: 2016
Authors: Khushbu Bansal, Shailendra Singh, Dharam Vir, Swati Sharma
10.5120/ijca2016908581

Khushbu Bansal, Shailendra Singh, Dharam Vir, Swati Sharma . Articulation Error Detection Techniques and Tools:. International Journal of Computer Applications. 136, 10 ( February 2016), 8-15. DOI=10.5120/ijca2016908581

@article{ 10.5120/ijca2016908581,
author = { Khushbu Bansal, Shailendra Singh, Dharam Vir, Swati Sharma },
title = { Articulation Error Detection Techniques and Tools: },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 10 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 8-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number10/24187-2016908581/ },
doi = { 10.5120/ijca2016908581 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:36:42.428371+05:30
%A Khushbu Bansal
%A Shailendra Singh
%A Dharam Vir
%A Swati Sharma
%T Articulation Error Detection Techniques and Tools:
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 10
%P 8-15
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Speech is the major source of communication. Articulation errors affect a person’s speech in adverse way. Speech language pathologists have to calculate the articulation errors manually amongst the persons suffering from speech problems. This task is very time consuming and exhaustive. Therefore, a system needs to automate this task. This paper presents all the advancements done in the field of speech recognition right from speech classification, feature extraction, speech models and tools by which an articulation error detection system can be built. The objective of this paper is to compare various methods by which an efficient articulation error detection system can be formulated.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Speech recognition articulation errors picture naming task feature extraction hidden markov model vector quantization.

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