Comparison between fuzzy and NN method for speech emotion recognition
This paper discusses an approach towards automatic recognition of emotion in speech which is adopted into a system named Voice Driven Emotion Recognizer Mobile Phone (VDERM). First, a design for the emotion recognizer is proposed. LPC analysis algorithm has been used for the speech emotion feature e...
| Main Authors: | , , |
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| Format: | Article |
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2005
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| Online Access: | http://shdl.mmu.edu.my/2387/ |
| _version_ | 1848790042075463680 |
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| author | Razak,, AA Abidin, , MIZ Komiya,, R |
| author_facet | Razak,, AA Abidin, , MIZ Komiya,, R |
| author_sort | Razak,, AA |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | This paper discusses an approach towards automatic recognition of emotion in speech which is adopted into a system named Voice Driven Emotion Recognizer Mobile Phone (VDERM). First, a design for the emotion recognizer is proposed. LPC analysis algorithm has been used for the speech emotion feature extraction. A total of 18 speech features have been selected to represent each emotion. A database consisting of emotional Malay and English, male and female voice samples have been developed for training and recognition purposes, Two recognition methods namely neural network and fuzzy model have been experimented and compared. The results show that both methods have their own advantage and disadvantage in application to emotion recognition. A recognition rate of up 60% is achievable by using these computer methods which is sufficient based on the recognition rate achieved by human. |
| first_indexed | 2025-11-14T18:06:19Z |
| format | Article |
| id | mmu-2387 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:06:19Z |
| publishDate | 2005 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-23872011-08-22T07:07:33Z http://shdl.mmu.edu.my/2387/ Comparison between fuzzy and NN method for speech emotion recognition Razak,, AA Abidin, , MIZ Komiya,, R QA75.5-76.95 Electronic computers. Computer science This paper discusses an approach towards automatic recognition of emotion in speech which is adopted into a system named Voice Driven Emotion Recognizer Mobile Phone (VDERM). First, a design for the emotion recognizer is proposed. LPC analysis algorithm has been used for the speech emotion feature extraction. A total of 18 speech features have been selected to represent each emotion. A database consisting of emotional Malay and English, male and female voice samples have been developed for training and recognition purposes, Two recognition methods namely neural network and fuzzy model have been experimented and compared. The results show that both methods have their own advantage and disadvantage in application to emotion recognition. A recognition rate of up 60% is achievable by using these computer methods which is sufficient based on the recognition rate achieved by human. 2005 Article NonPeerReviewed Razak,, AA and Abidin, , MIZ and Komiya,, R (2005) Comparison between fuzzy and NN method for speech emotion recognition. Third International Conference on Information Technology and Applications, Vol 1, Proceedings. pp. 297-302. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Razak,, AA Abidin, , MIZ Komiya,, R Comparison between fuzzy and NN method for speech emotion recognition |
| title | Comparison between fuzzy and NN method for speech emotion recognition |
| title_full | Comparison between fuzzy and NN method for speech emotion recognition |
| title_fullStr | Comparison between fuzzy and NN method for speech emotion recognition |
| title_full_unstemmed | Comparison between fuzzy and NN method for speech emotion recognition |
| title_short | Comparison between fuzzy and NN method for speech emotion recognition |
| title_sort | comparison between fuzzy and nn method for speech emotion recognition |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/2387/ |