• Journal of Multimedia Information System
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• v.8 no.1
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• pp.75-78
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• 2021

This paper will explain the importance of using interactive prototyping tools in the HCI design process. The Future of HCI education project performed by ACM SIGCHI shows that students recognize that prototyping, especially paper prototyping and interactive prototyping, are both very important. Two widely-used prototyping tools in academy, Balsamiq and Oven, will be compared and rated by students according to their preferences. We choose the Balsamiq as our design tool because Oven can be designed on the web but applications cannot be designed directly on Mac or Windows. The Balsamiq tool will help you understand the task process of UI work and highlight the benefits of digital prototyping to test the execution of expected results in a fast fashion compared to high-level prototyping. We also present the outcome of this work through two case studies. In particular, the smart mirror project with voice recognition function shows the effectiveness of the proposed method as an example.

• Annual Conference of KIPS
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• 2009.04a
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• pp.138-141
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• 2009

모바일 명함 관리 시스템은 간편하게 모바일 기기를 이용하여 명함을 등록하고 검색할 수 있으나 모바일 기기의 특징상 화면이 작고 정보를 이용하기 위해서는 펜을 이용하여 검색어를 입력해야하는 불편함이 있다. 이를 해결하기 위해 명령을 음성으로 처리하고자하는 VUI(Voice User Interface)의 필요성이 증가하였다. 또한 모바일 기기의 메모리 공간상의 제약으로 인한 음성인식엔진 탑재의 어려움이 있다. 이에 본 논문에서는 모바일 단말기로부터 음성을 입력받아 인식결과를 모바일 단말기로 되돌려 주는 음성인식 시스템을 구축하고 본 인식시스템과 모바일 클라이언트 시스템을 분산처리 가능한 웹서비스 환경으로 구성하였다.

• Annual Conference of KIPS
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• 2007.05a
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• pp.735-738
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• 2007

컴퓨팅 기술의 발전에 따라 유비쿼터스 시대로의 이행이 가속화되고 있다. 이에 따라 홈 네트워크 분야에 대한 연구와 상용화를 위한 노력이 활발해지고 있다. 이와 더불어 가전기기들의 종류는 다양해지고 복잡해지면서 사용자들의 가전기기 이용에 있어 사용법을 익혀야하는 어려움이 있다. 이러한 문제점을 해결하기 위한 일환으로 디지털 장치들을 편하게 사용하기 위한 멀티 모달 사용자 인터페이스가 요구되고 있다. 본 논문에서 네트워크 가전기기 제어가 가능한 홈 네트워크 미들웨어인 UPnP를 사용하여 VoiceXML을 통한 음성인식기반 사용자 인터페이스와 디지털 장치 제어 시스템을 제안하고 구현한 후 실험하였다.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.573-585
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• 2018

Services for navigation and entertainment through AI-based voice user interface devices are becoming popular in the connected car system. Given the classification of VUI agent developers as IT companies and automakers, this study explores attributes of agent persona and user experience that impact the driver's perceived safety and satisfaction. Participants of a car simulator experiment performed entertainment and navigation tasks, and evaluated the perceived safety and satisfaction. Results of regression analysis showed that credibility of the agent developer, warmth and attractiveness of agent persona, and efficiency and care of the UX dimension showed significant impact on the perceived safety. The determinants of perceived satisfaction were unity of auto-agent makers and gender as predisposing factors, distance in the agent persona, and convenience, efficiency, ease of use, and care in the UX dimension. The contributions of this study lie in the discovery of the factors required for developing conversational VUI into the autonomous driving environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.329-332
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.280-283
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1020-1026
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• 2005

In the era of ubiquitous computing, human-friendly man-machine interface is getting more attention due to its possibility to offer convenient services. For this, in this paper, we introduce a 'Half-Mirror Interface System (HMIS)' as a novel type of human-friendly man-machine interfaces. Basically, HMIS consists of half-mirror, USB-Webcam, microphone, 2ch-speaker, and high-speed processing unit. In our HMIS, two principal operation modes are selected by the existence of the user in front of it. The first one, 'mirror-mode', is activated when the user's face is detected via USB-Webcam. In this mode, HMIS provides three basic functions such as 1) make-up assistance by magnifying an interested facial component and TTS (Text-To-Speech) guide for appropriate make-up, 2) Daily weather information provider via WWW service, 3) Health monitoring/diagnosis service using Chinese medicine knowledge. The second one, 'display-mode' is designed to show decorative pictures, family photos, art paintings and so on. This mode is activated when the user's face is not detected for a time being. In display-mode, we also added a 'healing-window' function and 'healing-music player' function for user's psychological comfort and/or relaxation. All these functions are accessible by commercially available voice synthesis/recognition package.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.134-139
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• 2021

Currently, the autonomous vehicle market is commercializing a level 3 autonomous vehicle, but it still requires the attention of the driver. After the level 3 autonomous driving, the most notable aspect of level 4 autonomous vehicles is vehicle stability. This is because, unlike Level 3, autonomous vehicles after level 4 must perform autonomous driving, including the driver's carelessness. Therefore, in this paper, we propose the Emergency-notification and Driver-response Confirmation System(EDCS) for an autonomousvehicle safety that notifies the driver of an emergency situation and recognizes the driver's reaction in a situation where the driver is careless. The EDCS uses the emergency situation delivery module to make the emergency situation to text and transmits it to the driver by voice, and the driver response confirmation module recognizes the driver's reaction to the emergency situation and gives the driver permission Decide whether to pass. As a result of the experiment, the HMM of the emergency delivery module learned speech at 25% faster than RNN and 42.86% faster than LSTM. The Tacotron2 of the driver's response confirmation module converted text to speech about 20ms faster than deep voice and 50ms faster than deep mind. Therefore, the emergency notification and driver response confirmation system can efficiently learn the neural network model and check the driver's response in real time.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.139-146
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• 2009

This paper addresses a modified spectral subtraction schemes which is suitable to speech recognition under low signal-to-noise ratio (SNR) noisy environment such as the automatic speech recognition (ASR) system in car. The conventional spectral subtraction schemes rely on the SNR such that attenuation is imposed on that part of the spectrum that appears to have low SNR, and accentuation is made on that part of high SNR. However, such postulation is adequate for high SNR environment, it is grossly inadequate for low SNR scenarios such as that of car environment. Proposed methods focused specifically to low SNR noisy environment by using weighting function for enhancing speech dominant region in speech spectrum. Experimental results by using voice commands for car show the superior performance of the proposed method over conventional methods.

• Journal of KIISE
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• v.42 no.11
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• pp.1372-1379
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• 2015

This paper presents an analysis of feature extraction methods used for distinguishing the speech of patients with cleft palates and people with normal palates. This research is a basic study on the development of a software system for automatic recognition and restoration of speech disorders, in pursuit of improving the welfare of speech disabled persons. Monosyllable voice data for experiments were collected for three groups: normal speech, cleft palate speech, and simulated clef palate speech. The data consists of 14 basic Korean consonants, 5 complex consonants, and 7 vowels. Feature extractions are performed using three well-known methods: LPC, MFCC, and PLP. The pattern recognition process is executed using the acoustic model GMM. From our experiments, we concluded that the MFCC method is generally the most effective way to identify speech distortions. These results may contribute to the automatic detection and correction of the distorted speech of cleft palate patients, along with the development of an identification tool for levels of speech distortion.