Development of Secure Web System with Voice Interface to Identify Child Speakers

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In this study, the web-based system identifying child speakers, which can be adopted in web filtering system to protect children from the dangers of the Internet, has been developed as follows : (1) The collection of actual utterances was organized by using our voice-enabled web system. (2) The prototype system having the HMM-based classifier was developed. (3) The HMM-based method and the human's hearing abilities in distinguishing between child and adult utterances were compared. (4) We considered the linguistic features that help distinguish between children and adults. (5) The classifier based on combining 24-class HMMs (Hidden Markov Models) and SVMs (Support Vector Machines) was proposed. In the experiments, we proved improvements in accuracies in identifying child speakers by using voices captured from real web users.