| dc.contributor.author | M. N., Hasrul | |
| dc.contributor.author | M, Hariharan, Dr. | |
| dc.contributor.author | Sazali, Yaacob, Prof. Dr. | |
| dc.date.accessioned | 2012-10-11T04:14:04Z | |
| dc.date.available | 2012-10-11T04:14:04Z | |
| dc.date.issued | 2012-02-27 | |
| dc.identifier.citation | p. 217-222 | en_US |
| dc.identifier.isbn | 978-145771989-9 | |
| dc.identifier.uri | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6179008 | |
| dc.identifier.uri | http://dspace.unimap.edu.my/123456789/21318 | |
| dc.description | Link to publisher's homepage at http://ieeexplore.ieee.org/ | en_US |
| dc.description.abstract | Affective (Emotional) state of a person is very important in medical application due to the fact that it can indicate the stress level of an individual. This can be done through manipulating the speech signal of
individual that had been exposed to certain environment. Nowadays, emotion recognition in speech is a topic worth exploring in understanding how human being react and
interact with the environment and towards each other which still remains to be one of the extreme scientific challenges. This paper will review on some of the most common speech features used in conveying emotions from
speech signal. Also, presented are some of the effective techniques which are used to classify speech based on their emotions. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.relation.ispartofseries | Proceedings of the International Conference on Biomedical Engineering (ICoBE 2012) | en_US |
| dc.subject | Speech signal | en_US |
| dc.subject | Electroglottograph (EGG) signals | en_US |
| dc.subject | Recognition of emotion | en_US |
| dc.subject | Classification algorithm | en_US |
| dc.title | Human Affective (Emotion) behaviour analysis using speech signals: A review | en_US |
| dc.type | Working Paper | en_US |
| dc.contributor.url | kids.hasrul@gmail.com | en_US |
