An orthogonal least square approach to select features of infant cry with asphyxia
An investigation into the feature extraction and selection of infant cry with asphyxia is presented in this paper. The feature of the cry signal was extracted using mel frequency cepstrum coefficient (MFCC) analysis and the significant coefficients were selected using orthogonal least square (OLS) a...
| Published in: | Proceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
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IEEE Computer Society
2010
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84863150351&doi=10.1109%2fCSPA.2010.5545321&partnerID=40&md5=be00c0d56b73022c995fdc05f3a15764 |
| Summary: | An investigation into the feature extraction and selection of infant cry with asphyxia is presented in this paper. The feature of the cry signal was extracted using mel frequency cepstrum coefficient (MFCC) analysis and the significant coefficients were selected using orthogonal least square (OLS) algorithm. The effect of varying the number of MFCC filter banks on the feature selection was examined. It was found that the best set of coefficients could be achieved when 40 filter banks were used. © 2010 IEEE. |
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| ISSN: | |
| DOI: | 10.1109/CSPA.2010.5545321 |