Publication:
Infant cry recognition system: A comparison of system performance based on Mel frequency and linear prediction cepstral coefficients

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dc.citedby42
dc.contributor.authorAbdulaziz Y.en_US
dc.contributor.authorAhmad S.M.S.en_US
dc.contributor.authorid57207857499en_US
dc.contributor.authorid24721182400en_US
dc.date.accessioned2023-12-28T07:17:52Z
dc.date.available2023-12-28T07:17:52Z
dc.date.issued2010
dc.description.abstractThis paper describes the architecture of an automatic infant cry recognition system which main task is to identify and differentiate between pain and non-pain cries belonging to infants. The recognition system is mainly based on feed forward neural network architecture which is trained with the scaled conjugate gradient algorithm. This paper presents an in depth comparison of system performance whereby two different sets of features, namely Mel Frequency Cepstral Coefficient (MFCC) and Linear Prediction Cepstral Coefficients (LPCC) are extracted from the audio samples of infant's cries and are fed into the recognition module. The system accuracy reported in this study varies from 57% up to 76.2% under different parameter settings. The results demonstrated that in general, the infant cry recognition system performs better by using the MPCC feature sets. �2010 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo5466907
dc.identifier.doi10.1109/INFRKM.2010.5466907
dc.identifier.epage263
dc.identifier.scopus2-s2.0-77953877115
dc.identifier.spage260
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77953877115&doi=10.1109%2fINFRKM.2010.5466907&partnerID=40&md5=1b3d38bf4450fcc234b721c0f74d5e0f
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29647
dc.pagecount3
dc.sourceScopus
dc.sourcetitleProceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10
dc.subjectAutomatic recognition of infant cry
dc.subjectFeed-forward neural network
dc.subjectLinear prediction cepstral coefficients
dc.subjectMel-frequency cepstral coefficients
dc.subjectConjugate gradient method
dc.subjectExtraction
dc.subjectFeedforward neural networks
dc.subjectInformation retrieval
dc.subjectKnowledge management
dc.subjectNatural language processing systems
dc.subjectSpeech recognition
dc.subjectAudio samples
dc.subjectAutomatic recognition
dc.subjectFeature sets
dc.subjectInfant cry
dc.subjectInfant cry recognition
dc.subjectLinear prediction cepstral coefficients
dc.subjectMain tasks
dc.subjectMel-frequency cepstral coefficients
dc.subjectParameter setting
dc.subjectPerformance based
dc.subjectRecognition systems
dc.subjectScaled conjugate gradient algorithm
dc.subjectSystem accuracy
dc.subjectForecasting
dc.titleInfant cry recognition system: A comparison of system performance based on Mel frequency and linear prediction cepstral coefficientsen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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