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Vowel Analysis for Identifying Expression of Emotions in Odia-Spoken-Language

by Sanghamitra Mohanty, Basanta Kumar Swain
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 3
Year of Publication: 2012
Authors: Sanghamitra Mohanty, Basanta Kumar Swain
10.5120/6087-8253

Sanghamitra Mohanty, Basanta Kumar Swain . Vowel Analysis for Identifying Expression of Emotions in Odia-Spoken-Language. International Journal of Computer Applications. 43, 3 ( April 2012), 47-52. DOI=10.5120/6087-8253

@article{ 10.5120/6087-8253,
author = { Sanghamitra Mohanty, Basanta Kumar Swain },
title = { Vowel Analysis for Identifying Expression of Emotions in Odia-Spoken-Language },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 3 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 47-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number3/6087-8253/ },
doi = { 10.5120/6087-8253 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:32:28.996321+05:30
%A Sanghamitra Mohanty
%A Basanta Kumar Swain
%T Vowel Analysis for Identifying Expression of Emotions in Odia-Spoken-Language
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 3
%P 47-52
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Speech can be described as an act of producing voice through the use of the vocal folds and vocal apparatus to create a linguistic act for conveying intended information. Speech is a subtle and rich communication that transfers not only the linguistic information, but also information about the personality and the emotional state of the speaker. The objective of this study is to analyse the effect of vocal characteristics like duration of vowels, mean pitch, jitter and shimmer of vowels in different Oriya spoken emotional speech uttered by female & male speakers. This paper also used FFBPNN as a classifier to identify an emotion out of five emotional categories such as Normal, Santa, Karuna, Raoudra, Shringar using Jitter and Shimmer variants as feature vectors. The supervised classifier achieved 86. 88% accuracy rate in vowel domain. The emotional speech corpus is recorded from several semi-professionals actors within range of 22-35 years old.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Ffbpnn Jitter Shimmer Emotion