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...
| Main Authors: | , , |
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| Format: | Article |
| Published: |
International Scientific Academy of Engineering & Technology
2013
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| Subjects: | |
| 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 |
| Summary: | 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. |
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