• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.583-590
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• 2016

Recently, the rapidly increasing interest in IoT in almost all areas of casual human life has led to wide acceptance of speech recognition as a means of HCI. Simultaneously, the demand for speech recognition systems for mobile environments is increasing rapidly. The server-based speech recognition systems are typically fast and show high recognition rates; however, an internet connection is necessary, and complicated server computation is required since a voice is recognized by units of words that are stored in server databases. In this paper, we present a novel method for recognizing the Korean vowel 'ㅗ', as a part of a phoneme based Korean speech recognition system. The proposed method involves analyses of waveform patterns in the time domain instead of the frequency domain, with consequent reduction in computational cost. Elementary algorithms for detecting typical waveform patterns of 'ㅗ' are presented and combined to make final decisions. The experimental results show that the proposed method can achieve 89.9% recognition accuracy.

• 재활복지
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• v.20 no.1
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• pp.211-233
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• 2016

The purpose of this study is to figure out problems and to suggest improvement scheme by examining 31 of the disabled who used power wheelchair developed for safe moving and standing support. The results are as follows. First, standing power wheelchair that enables the disabled to sit and stand up was developed. It can also be used as means of transportation for moving in narrow space and in a short distance. In the usability test of this prototype, two groups were respectively examined in 60 evaluation items. One group consisted of 16 people with disabilities using manual wheelchairs. And the other one consisted of 15 people with disabilities using automatic wheelchairs. The entire average figure of two groups was shown to be 2.72 and standard deviation was 0.820. Specifically, the average figure of the group in manual wheelchair was 2.85 and the one of the other group in automatic wheelchair was 2.57. And both group replied that the move to stand up and sit on both types of wheelchair was the most inconvenient thing. It shows why ergonomic design for persons with under extremity disabilities to stand up and sit is needed. Second, with further study based on the results of usability test of the disabled, it will make contribution to increase the quality of people with disabilities by helping them move and do daily lives on their own.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.29-37
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• 2016

Humans develop and maintain relationship through communication. Communication is largely divided into verbal communication and non-verbal communication. Verbal communication involves the use of a language or characters, while non-verbal communication utilizes body language. We use gestures with language together in conversations of everyday life. Gestures belong to non-verbal communication, and can be offered using a variety of shapes and movements to deliver an opinion. For this reason, gestures are spotlighted as a means of implementing an NUI/NUX in the fields of HCI and HRI. In this paper, using Kinect and the geometric features of the hand, we propose a method for recognizing the number of fingers and detecting the hand area. A Kinect depth image can be used to detect the hand region, with the finger number identified by comparing the distance of outline and the central point of a hand. Average recognition rate for recognizing the number of fingers is 98.5%, from the proposed method, The proposed method would help enhancing the functionality of the human computer interaction by increasing the expression range of gestures.