• Title/Summary/Keyword: Elderly voice signal processing

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Elderly Speech Signal Processing: A Systematic Review for Analysis of Gender Innovation (노인음성신호처리: 젠더혁신 분석에 대한 체계적 문헌고찰)

  • Lee, JiYeoun
    • Journal of Convergence for Information Technology
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    • v.9 no.8
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    • pp.148-154
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    • 2019
  • The purpose of this study is to review systematically the literatures on the research of the elderly speech signal processing based on the domestic gender innovation and to introduce the utility and innovation of the gender analysis methods. From 2000 to present, among the 37 research papers published in the Korean Journal, 25 papers were selected according to the inclusion and exclusion criteria. And gender analysis methods were applied to gender research subject and design. Research results show diversity of research field and high gender recognition of R & D team are needed in research and development of engineering of gender innovation perspective. In addition, government-level regulation and research funding should be systematically applied to gender innovation research processes in the elderly voice signal processing and various gender innovation projects. In the future gender innovation in the elderly speech signal processing can contribute to the creation of a new market by developing a voice recognition system and service that reflects the needs of both men and women.

Gender Analysis in Elderly Speech Signal Processing (노인음성신호처리에서의 젠더 분석)

  • Lee, JiYeoun
    • 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.

A Study on Traffic Light Detection (TLD) as an Advanced Driver Assistance System (ADAS) for Elderly Drivers

  • Roslan, Zhafri Hariz;Cho, Myeon-gyun
    • International Journal of Contents
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    • v.14 no.2
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    • pp.24-29
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    • 2018
  • In this paper, we propose an efficient traffic light detection (TLD) method as an advanced driver assistance system (ADAS) for elderly drivers. Since an increase in traffic accidents is associated with the aging population and an increase in elderly drivers causes a serious social problem, the provision of ADAS for older drivers via TLD is becoming a necessary(Ed: verify word choice: necessary?) public service. Therefore, we propose an economical TLD method that can be implemented with a simple black box (built in camera) and a smartphone in the near future. The system utilizes a color pre-processing method to differentiate between the stop and go signals. A mathematical morphology algorithm is used to further enhance the traffic light detection and a circular Hough transform is utilized to detect the traffic light correctly. From the simulation results of the computer vision and image processing based on a proposed algorithm on Matlab, we found that the proposed TLD method can detect the stop and go signals from the traffic lights not only in daytime, but also at night. In the future, it will be possible to reduce the traffic accident rate by recognizing the traffic signal and informing the elderly of how to drive by voice.

Gendered innovation for algorithm through case studies (음성·영상 신호 처리 알고리즘 사례를 통해 본 젠더혁신의 필요성)

  • Lee, JiYeoun;Lee, Heisook
    • Journal of Digital Convergence
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    • v.16 no.12
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    • pp.459-466
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    • 2018
  • Gendered innovations is a term used by policy makers and academics to refer the process of creating better research and development (R&D) for both men and women. In this paper, we analyze the literatures in image and speech signal processing that can be used in ICT, examine the importance of gendered innovations through case study. Therefore the latest domestic and foreign literature related to image and speech signal processing based on gender research is searched and a total of 9 papers are selected. In terms of gender analysis, research subjects, research environment, and research design are examined separately. Especially, through the case analysis of algorithms of the elderly voice signal processing, machine learning, machine translation technology, and facial gender recognition technology, we found that there is gender bias in existing algorithms, and which leads to gender analysis is required. We also propose a gendered innovations method integrating sex and gender analysis in algorithm development. Gendered innovations in ICT can contribute to the creation of new markets by developing products and services that reflect the needs of both men and women.