Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/12181
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hariharan, Muthusamy | - |
dc.contributor.author | Paulraj, Murugesa Pandiyan, Assoc. Prof. | - |
dc.contributor.author | Sazali, Yaacob, Prof. Dr. | - |
dc.date.accessioned | 2011-06-09T04:44:14Z | - |
dc.date.available | 2011-06-09T04:44:14Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | International Journal of Biomedical Engineering and Technology, vol.6(1), 2011, pages 46-57 | en_US |
dc.identifier.issn | 1752-6418 | - |
dc.identifier.uri | http://www.inderscience.com/search/index.php?action=record&rec_id=40452 | - |
dc.identifier.uri | http://dspace.unimap.edu.my/123456789/12181 | - |
dc.description | Link to publisher's homepage at http://www.inderscience.com/ | en_US |
dc.description.abstract | This paper proposes a feature extraction method based on time-domain energy variation for the detection of vocal fold pathology. In this work, two different vocal fold problems (vocal fold paralysis and edema) are taken for analysis and in either case, a two-class pattern recognition problem is investigated. The normal and pathological speech samples are used from Massachusetts Eye and Ear Infirmary database. Probabilistic Neural Network (PNN) is employed for the classification. The experimental results show that the proposed features give very promising classification accuracy of 90% and can be used to detect the vocal fold paralysis and edema clinically. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Inderscience Publisher | en_US |
dc.subject | Vocal fold pathology | en_US |
dc.subject | Acoustic analysis | en_US |
dc.subject | Time-domain energy features | en_US |
dc.subject | Probabilistic Neural Network (PNN) | en_US |
dc.subject | Probabilistic neural network | en_US |
dc.subject | Vocal fold paralysis | en_US |
dc.subject | Edema | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Speech signals | en_US |
dc.subject | Voice | en_US |
dc.title | Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network | en_US |
dc.type | Article | en_US |
dc.contributor.url | paul@unimap.edu.my | en_US |
dc.contributor.url | wavelet.hari@gmail.com | en_US |
dc.contributor.url | s.yaacob@unimap.edu.my | en_US |
Appears in Collections: | School of Mechatronic Engineering (Articles) Sazali Yaacob, Prof. Dr. Hariharan Muthusamy, Dr. Paulraj Murugesa Pandiyan, Assoc. Prof. Dr. |
Files in This Item:
File | Description | Size | Format | |
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abstract detection of vocal fold paralysis and enema using time domain features and probabilistic neural network.pdf | 23.53 kB | Adobe PDF | View/Open |
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