Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN
Speech emotion recognition field is growing due to the increasing needs for effective human-computer interaction. There are many approaches in term of features extraction methods coupled with classifiers to obtain optimum performance. However, none can claim superiority as it is very data-depen...
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2013
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| Online Access: | http://irep.iium.edu.my/31010/ http://irep.iium.edu.my/31010/ http://irep.iium.edu.my/31010/1/Table_of_Content.pdf http://irep.iium.edu.my/31010/2/106.pdf |
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iium-31010 |
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iium-310102015-09-09T02:40:58Z http://irep.iium.edu.my/31010/ Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN Kamaruddin, Norhaslinda Abdul Rahman, Abdul Wahab BF511 Affection. Feeling. Emotion H61.8 Communication of information T58.5 Information technology Speech emotion recognition field is growing due to the increasing needs for effective human-computer interaction. There are many approaches in term of features extraction methods coupled with classifiers to obtain optimum performance. However, none can claim superiority as it is very data-dependant and domain oriented. In this paper, the appropriate sets of features are investigated using segregation method and feature ranking algorithm of Automatic Relevance Determination (ARD) [1]. Two popular classifiers of Multi Layer Perceptron (MLP) [2] and Generic Self-organizing Fuzzy Neural Network (GenSoFNN) [3] are employed to discriminate emotions in the data corpus used in the FAU Aibo Emotion Corpus [4, 5]. The experimental results shows that Mel Frequency Cepstral Coefficient (MFCC) [6] features are able to yield comparable accuracy with baseline result [5]. In addition, it is observed that MLP can perform slightly better than GenSoFNN. Hence, such system envisages that appropriate combination of features extracted with good classifiers is fundamental for the good speech emotion recognition system. 2013 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/31010/1/Table_of_Content.pdf application/pdf en http://irep.iium.edu.my/31010/2/106.pdf Kamaruddin, Norhaslinda and Abdul Rahman, Abdul Wahab (2013) Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN. In: The 4th International Conference on Information & Communication Technology for the Muslim World (ICT4M), 25-27 Mar 2013, Rabat, Moroco. http://ict4m.org/ |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| language |
English English |
| topic |
BF511 Affection. Feeling. Emotion H61.8 Communication of information T58.5 Information technology |
| spellingShingle |
BF511 Affection. Feeling. Emotion H61.8 Communication of information T58.5 Information technology Kamaruddin, Norhaslinda Abdul Rahman, Abdul Wahab Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN |
| description |
Speech emotion recognition field is growing due to
the increasing needs for effective human-computer interaction.
There are many approaches in term of features extraction
methods coupled with classifiers to obtain optimum
performance. However, none can claim superiority as it is very
data-dependant and domain oriented. In this paper, the
appropriate sets of features are investigated using segregation
method and feature ranking algorithm of Automatic Relevance
Determination (ARD) [1]. Two popular classifiers of Multi
Layer Perceptron (MLP) [2] and Generic Self-organizing Fuzzy
Neural Network (GenSoFNN) [3] are employed to discriminate
emotions in the data corpus used in the FAU Aibo Emotion
Corpus [4, 5]. The experimental results shows that Mel
Frequency Cepstral Coefficient (MFCC) [6] features are able to
yield comparable accuracy with baseline result [5]. In addition,
it is observed that MLP can perform slightly better than
GenSoFNN. Hence, such system envisages that appropriate
combination of features extracted with good classifiers is
fundamental for the good speech emotion recognition system. |
| format |
Conference or Workshop Item |
| author |
Kamaruddin, Norhaslinda Abdul Rahman, Abdul Wahab |
| author_facet |
Kamaruddin, Norhaslinda Abdul Rahman, Abdul Wahab |
| author_sort |
Kamaruddin, Norhaslinda |
| title |
Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN |
| title_short |
Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN |
| title_full |
Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN |
| title_fullStr |
Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN |
| title_full_unstemmed |
Emulating human cognitive approach for speech emotion recognition using MLP and GenSoFNN |
| title_sort |
emulating human cognitive approach for speech emotion recognition using mlp and gensofnn |
| publishDate |
2013 |
| url |
http://irep.iium.edu.my/31010/ http://irep.iium.edu.my/31010/ http://irep.iium.edu.my/31010/1/Table_of_Content.pdf http://irep.iium.edu.my/31010/2/106.pdf |
| first_indexed |
2023-09-18T20:45:14Z |
| last_indexed |
2023-09-18T20:45:14Z |
| _version_ |
1777409630970839040 |