Feature extraction of speech signal and heartbeat detection in angry emotion identification

Angry is one of emotions that play an essential role in decision making, perception, learning and more. This paper detects the angry emotion by analyzing and recognizing angry speech signal as well as detecting the heartbeat condition. The speech database was uttered by various speakers in different...

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Main Authors:	Mohamed, Masnani, Lee, Chee Chuan, Ahmad, Ida Laila
Format:	Article
Published:	International Scientific Academy of Engineering & Technology 2013
Subjects:	TK5101-5865 Telecommunication. Telegraph.
Online Access:	http://www.isaet.org/proceeding.php?catid=58&type=2&mode=detail http://www.isaet.org/proceeding.php?catid=58&type=2&mode=detail http://eprints.uthm.edu.my/6126/1/Feature_Extraction_of_Speech_Signal.pdf

id	uthm-6126
recordtype	eprints
spelling	uthm-61262014-12-17T08:26:37Z Feature extraction of speech signal and heartbeat detection in angry emotion identification Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila TK5101-5865 Telecommunication. Telegraph. Angry is one of emotions that play an essential role in decision making, perception, learning and more. This paper detects the angry emotion by analyzing and recognizing angry speech signal as well as detecting the heartbeat condition. The speech database was uttered by various speakers in different gender and emotions. For the analyzing experiment, several digital signal processing methods such as autocorrelation and linear predication technique was introduced to analyze the features. Then, Artificial Neural Network (ANN) was used to classify each parameter features such as mean fundamental frequency, maximum fundamental frequency, standard deviation fundamental frequency, mean amplitude, pause length ratio and first formant frequency to recognize the emotion. Meanwhile, a heartbeat monitoring circuit was developed to measure the heartbeat. The accuracy of the result has achieved over than 80 percent during emotional recognition test. This method can be used further to recognize angry emotion of patient during counseling session. International Scientific Academy of Engineering & Technology 2013 Article NonPeerReviewed application/pdf http://eprints.uthm.edu.my/6126/1/Feature_Extraction_of_Speech_Signal.pdf http://www.isaet.org/proceeding.php?catid=58&type=2&mode=detail Mohamed, Masnani and Lee, Chee Chuan and Ahmad, Ida Laila (2013) Feature extraction of speech signal and heartbeat detection in angry emotion identification. International Journal of Computer Science and Electronics Engineering (IJCSEE), 1 (1). ISSN 2320–4028 http://eprints.uthm.edu.my/6126/
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Tun Hussein Onn Malaysia
building	UTHM Institutional Repository
collection	Online Access
topic	TK5101-5865 Telecommunication. Telegraph.
spellingShingle	TK5101-5865 Telecommunication. Telegraph. Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila Feature extraction of speech signal and heartbeat detection in angry emotion identification
description	Angry is one of emotions that play an essential role in decision making, perception, learning and more. This paper detects the angry emotion by analyzing and recognizing angry speech signal as well as detecting the heartbeat condition. The speech database was uttered by various speakers in different gender and emotions. For the analyzing experiment, several digital signal processing methods such as autocorrelation and linear predication technique was introduced to analyze the features. Then, Artificial Neural Network (ANN) was used to classify each parameter features such as mean fundamental frequency, maximum fundamental frequency, standard deviation fundamental frequency, mean amplitude, pause length ratio and first formant frequency to recognize the emotion. Meanwhile, a heartbeat monitoring circuit was developed to measure the heartbeat. The accuracy of the result has achieved over than 80 percent during emotional recognition test. This method can be used further to recognize angry emotion of patient during counseling session.
format	Article
author	Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila
author_facet	Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila
author_sort	Mohamed, Masnani
title	Feature extraction of speech signal and heartbeat detection in angry emotion identification
title_short	Feature extraction of speech signal and heartbeat detection in angry emotion identification
title_full	Feature extraction of speech signal and heartbeat detection in angry emotion identification
title_fullStr	Feature extraction of speech signal and heartbeat detection in angry emotion identification
title_full_unstemmed	Feature extraction of speech signal and heartbeat detection in angry emotion identification
title_sort	feature extraction of speech signal and heartbeat detection in angry emotion identification
publisher	International Scientific Academy of Engineering & Technology
publishDate	2013
url	http://www.isaet.org/proceeding.php?catid=58&type=2&mode=detail http://www.isaet.org/proceeding.php?catid=58&type=2&mode=detail http://eprints.uthm.edu.my/6126/1/Feature_Extraction_of_Speech_Signal.pdf
first_indexed	2018-09-05T11:23:24Z
last_indexed	2018-09-05T11:23:24Z
_version_	1610766462404788224

Feature extraction of speech signal and heartbeat detection in angry emotion identification

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