2012
DOI: 10.1155/2012/983147 View full text |Buy / Rent full text
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Abstract: We make use of information inside infant’s cry signal in order to identify the infant’s psychological condition. Gaussian mixture models (GMMs) are applied to distinguish between healthy full-term and premature infants, and those with specific medical problems available in our cry database. Cry pattern for each pathological condition is created by using adapted boosting mixture learning (BML) method to estimate mixture model parameters. In the first experiment, test results demonstrate that the introduced adap… Show more

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“…Note that the same basic model of speech production ( Deller et al., 1993 ) in adults is used to find these measurements. Thus far, it has been shown that they are also effective in classifying healthy and sick infants based on our primary results ( Farsaie Alaie and Tadj, 2012 ). Moreover, we incorporate context information by adding dynamic features in this work, but they are not necessarily the most informative features for the intended pathology classification task.…”
Section: Feature Extractionmentioning
“…In our previous studies ( Farsaie Alaie and Tadj, 2012 , Alaie and Tadj, 2013 ), we have introduced a working prototype to train a GMM in an incremental and recursive manner; this method is called the adapted boosting mixture learning Method (BML). The proposed method trains finite mixture models by a pool of Gaussian components.…”
Section: Introductionmentioning
“…in EM-based sensitivity to [11][12][13][14][15][16][17]. In our previous work [18], we made use of cry signals to distinguish between healthy and sick infants both full-term and premature. Most of the previous studies [11][12][13][14][15][16][17]19] concentrate on health status of infants via a binary classification task, but this paper focuses on identifying several different pathological conditions.…”
Section: Introducmentioning
“…extracted from the cries and the health problems of the child [2][3][4][5]. Various studies are currently under way to devise a tool that analyzes cries automatically, to diagnose neonatal pathologies [6][7][8].We are involved in the design of an automatic system for early diagnosis, called the Newborn Cry-based Diagnostic System (NCDS), which can detect certain pathologies in newborns at an early stage. The implementation of this system requires a database containing hundreds of cry signals.…”
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“…extracted from the cries and the health problems of the child [2][3][4][5]. Various studies are currently under way to devise a tool that analyzes cries automatically, to diagnose neonatal pathologies [6][7][8].…”
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