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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| Format: | Article |
| Language: | en |
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journalsweb.org
2013
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| Online Access: | http://eprints.uthm.edu.my/3544/1/AJ%202017%20%2877a%29%20Feature%20extraction%20of%20speech%20signal.pdf http://eprints.uthm.edu.my/3544/ |
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| _version_ | 1833417365009727488 |
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| author | Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila |
| author_facet | Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila |
| author_sort | Mohamed, Masnani |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my.uthm.eprints-3544 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2013 |
| publisher | journalsweb.org |
| record_format | eprints |
| spelling | my.uthm.eprints-35442021-11-18T06:24:01Z http://eprints.uthm.edu.my/3544/ Feature extraction of speech signal and heartbeat detection in angry emotion identification Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila TK7800-8360 Electronics 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. journalsweb.org 2013 Article PeerReviewed text en http://eprints.uthm.edu.my/3544/1/AJ%202017%20%2877a%29%20Feature%20extraction%20of%20speech%20signal.pdf 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). pp. 101-106. ISSN 2320 –401X |
| spellingShingle | TK7800-8360 Electronics Mohamed, Masnani Lee, Chee Chuan Ahmad, Ida Laila Feature extraction of speech signal and heartbeat detection in angry emotion identification |
| title | 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_short | 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 |
| topic | TK7800-8360 Electronics |
| url | http://eprints.uthm.edu.my/3544/1/AJ%202017%20%2877a%29%20Feature%20extraction%20of%20speech%20signal.pdf http://eprints.uthm.edu.my/3544/ |
| url_provider | http://eprints.uthm.edu.my/ |