• Journal of Digital Convergence
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• v.15 no.10
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• pp.467-483
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• 2017

The purpose of this study was to explore the role and meaning of smartphone in the context of daily life. This research focuses on the woman in twenties living in Hangzhou, China. As a result of research, smartphones affected the various parts of female users' daily lives such as consumption habits, ways of spending their times and ways of information gathering and communication. Nevertheless gender gap in smartphone use was much smaller than before in the quantitative aspect, women's use of smartphone in qualitative aspect such as the way of use and choice of contents showed previous gender role and gender value in society. Also, the results of the research, based on the case of China which emerges as a new IT powerhouse, have a significant implication for smartphone use in Korea.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.351-356
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• 2018

Changes in vocal cords due to aging can change the frequency of speech, and the speech signals of the elderly can be automatically distinguished from normal speech signals through various analyzes. The purpose of this study is to provide a tool that can be easily accessed by the elderly and disabled people who can be excluded from the rapidly changing technological society and to improve the voice recognition performance. In the study, the gender of the subjects was reported as sex analysis, and the number of female and male voice samples was used equally. In addition, the gender analysis was applied to set the voices of the elderly without using voices of all ages. Finally, we applied a review methodology of standards and reference models to reduce gender difference. 10 Korean women and 10 men aged 70 to 80 years old are used in this study. Comparing the F0 value extracted directly with the waveform and the F0 extracted with TF32 and the Wavesufer speech analysis program, Wavesufer analyzed the F0 of the elderly voice better than TF32. However, there is a need for a voice analysis program for elderly people. In conclusions, analyzing the voice of the elderly will improve speech recognition and synthesis capabilities of existing smart medical systems.