• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.41-43
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• 2021

Robot Operating System (ROS) has been a prominent and successful framework used in robotics business and academia.. However, the framework has long been focused and limited to navigation of robots and manipulation of objects in the environment. This focus leaves out other important field such as speech recognition, vision abilities, etc. Our goal is to take advantage of ROS capacity to integrate additional libraries of programming functions aimed at real-time computer vision with a depth-image camera. In this paper we will focus on the implementation of an upgraded vision with the help of a depth camera which provides a high quality data for a much enhanced and accurate understanding of the environment. The varied data from the cameras are then incorporated in ROS communication structure for any potential use. For this particular case, the system will use OpenCV libraries to manipulate the data from the camera and provide a face-detection capabilities to the robot, while navigating an indoor environment. The whole system has been implemented and tested on the latest technologies of Turtlebot3 and Raspberry Pi4.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.223-232
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• 2016

This study focuses on the new teaching assistance robot platform and the cloud-based education service model to support the server. In the client area we would like to use the teacher assistant robot in elementary school classrooms to utilize the language education service platform. Emerging IoT technology will be adopted to provide a comfortable classroom environment and various media interfaces. Extensive precedent review and case study have been conducted to identify basic requirements of proposed service platform. Embedded system and technology for image recognition, speech recognition, autonomous movement, display, touch screen, IR sensor, GPS, and temperature-humidity sensor were extensively investigated to complete the service. Key findings of this paper are optimized service platform with cloud server system and possibilities of potential smart classroom with intelligent robot by adopting IoT and BIM technology.

• Journal of The Korean Association of Information Education
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• v.20 no.4
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• pp.323-332
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• 2016

A robot's recognition and diagnosis of pronunciation and its speech are the most important interactions in RALL(Robot Assisted Language Learning). This study is to verify the effectiveness of robot TTS(Text to Sound) technology in assisting Korean English language learners to acquire a native-like accent by correcting the prosodic errors they commonly make. The child English language learners' F0 range and speaking rate in the 4th grade, a prosodic variable, will be measured and analyzed for any changes in accent. We compare whether robot with the currently available TTS technology appeared to be effective for the 4th graders and 1st graders who were not under the formal English learning with native speaker from the acoustic phonetic viewpoint. Two groups by repeating TTS of RALL responded to the speaking rate rather than F0 range.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.45-50
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• 2003

Recently, robots technique has been developed remarkably. Emotion recognition is necessary to make an intimate robot. This paper shows the simulator and simulation result which recognize or classify emotions by learning pitch pattern. Also, because the pitch is not sufficient for recognizing emotion, we added acoustic elements. For that reason, we analyze the relation between emotion and acoustic elements. The simulator is composed of the DRNN(Dynamic Recurrent Neural Network), Feature extraction. DRNN is a learning algorithm for pitch pattern.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.555-558
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• 2006

감정을 포함하고 있는 음성은 청자로 하여금 화자의 심리상태를 파악할 수 있게 하는 요소 중에 하나이다. 음성신호에 포함되어 있는 감정을 인식하여 사람과 로봇과의 원활한 감성적 상호작용을 위하여 특징을 추출하고 감정을 분류한 방법을 제시한다. 음성신호로부터 음향정보 및 운율정보인 기본 특징들을 추출하고 이로부터 계산된 통계치를 갖는 특징벡터를 입력으로 support vector machine (SVM) 기반의 패턴분류기를 사용하여 6가지의 감정- 화남(angry), 지루함(bored), 기쁨(happy), 중립(neutral), 슬픔(sad) 그리고 놀람(surprised)으로 분류한다. SVM에 의한 인식실험을 한 경우 51.4%의 인식률을 보였고 사람의 판단에 의한 경우는 60.4%의 인식률을 보였다. 또한 화자가 판단한 감정 데이터베이스의 감정들을 다수의 청자가 판단한 감정 상태로 변경한 입력을 SVM에 의해서 감정을 분류한 결과가 51.2% 정확도로 감정인식하기 위해 사용한 기본 특징들이 유효함을 알 수 있다.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.390-397
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• 2003

We propose a humanoid active audition system which detects the direction of sound using just three microphones. Compared with previous researches, this system which has a simpler algorithm and less microphone shows better performance. Moreover, it uses the fuzzy logic system to remove the reflective sound and makes the resultant improvement of confidence. In order to verify our system's performance, we install the proposed active audition system to the home service robot, called hombot II, which has been developed at the KIST(Korea Institute of Science and Technology), and confirm its excellent performance through the experiment.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.329-330
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• 2008

최근 음성인식률이 영어를 기준으로 97% 이상 높아짐에 따라 음성 인식을 사용한 여러서비스들이 등장하고 있다. 지능 로봇도 예외가 아니어서 많은 서비스 로봇, 지능형 로봇에 음성 인식 기술이 적용되고 있다. 본 논문에서는 수많은 음성 인식 기술 중에서 로봇 시스템에 맞는 시스템을 선택하고, 이를 효율적으로 운용할 수 있는 방법을 제시한다. 또한 직접 지능형 서비스 로봇을 만들면서 음성 인식이 로봇에서 얼마나 중요한 위치를 차지하고 있는지를 확인하였으며 단순한 단어, 문장을 인식하는 것에 그치는 것이 아니라 향후 대화를 통해 사람과 로봇의 커뮤니케이션이 가능한 시스템을 제시한다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.457-462
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• 2005

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is currently one of the most attractive technologies for all. However, unless we find a breakthrough to the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technology. Unlike the industrial robot of the past, today's robots require advanced technologies, such as soft computing, human-friendly interface, interaction technique, speech recognition, object recognition, and many others. In this study, we present a new technological concept named RCP(Robotic Cellular Phone), which combines RT & CP, in the vision of opening a new direction to the advance of CP, IT, and RT all together. RCP consists of 3 sub-modules. They are $RCP^{Mobility}$, $RCP^{Interaction}$, and $RCP^{Interaction}$. $RCP^{Mobility}$ is the main focus of this paper. It is an autonomous navigation system that combines RT mobility with CP. Through $RCP^{Mobility}$, we should be able to provide CP with robotic functionalities such as auto-charging and real-world robotic entertainments. Eventually, CP may become a robotic pet to the human being. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While Trajectory Controller is responsible for the wheel-based navigation of RCP, Self-Localization Controller provides localization information of the moving RCP. With the coordinate information acquired from RFID-based self-localization controller, Trajectory Controller refines RCP's movement to achieve better RCP navigations. In this paper, a prototype system we developed for $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results of the RCP navigation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.480-488
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• 2006

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is one of the most attractive technologies of today. However, unless we find a new breakthrough in the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technologies. Unlike the industrial robot of the past, today's robots require advanced features, such as soft computing, human-friendly interface, interaction technique, speech recognition object recognition, among many others. In this paper, we present a new technological concept named RCP (Robotic Cellular Phone) which integrates RT and CP in the vision of opening a combined advancement of CP, IT, and RT, RCP consists of 3 sub-modules. They are $RCP^{Mobility}$(RCP Mobility System), $RCP^{Interaction}$, and $RCP^{Integration}$. The main focus of this paper is on $RCP^{Mobility}$ which combines an autonomous navigation system of the RT mobility with CP. Through $RCP^{Mobility}$, we are able to provide CP with robotic functions such as auto-charging and real-world robotic entertainment. Ultimately, CP may become a robotic pet to the human beings. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While the former is responsible for the wheel-based navigation of RCP, the latter provides localization information of the moving RCP With the coordinates acquired from RFID-based self-localization controller, trajectory controller refines RCP's movement to achieve better navigation. In this paper, a prototype of $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results on the RCP navigation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.82-85
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• 2007

현재 가정을 비롯한 여러 분야에서 서비스 로봇(청소 로봇, 애완용 로봇, 멀티미디어 로봇 둥)의 사용이 증가하고 있는 시장상황을 보이고 있다. 개인용 서비스 로봇은 인간 친화적 특성을 가져야 그 선호도가 높아질 수 있는데 이를 위해서 사용자의 감정 인식 및 표현 기술은 필수적인 요소이다. 사람들의 감정 인식을 위해 많은 연구자들은 음성, 사람의 얼굴 표정, 생체신호, 제스쳐를 통해서 사람들의 감정 인식을 하고 있다. 특히, 음성을 인식하고 적용하는 것에 관한 연구가 활발히 진행되고 있다. 본 논문은 감정 인식 시스템을 두 가지 방법으로 제안하였다. 현재 많이 개발 되어지고 있는 음성인식 모듈을 사용하여 단어별 감정을 분류하여 감정 표현 시스템에 적용하는 것과 마이크로폰을 통해 습득된 음성신호로부터 특정들을 검출하여 Bayesian Learning(BL)을 적용시켜 normal, happy, sad, surprise, anger 등 5가지의 감정 상태로 패턴 분류를 한 후 이것을 동적 감정 표현 알고리즘의 입력값으로 하여 dynamic emotion space에 사람의 감정을 표현할 수 있는 ARM 플랫폼 기반의 음성 인식 및 감정 표현 시스템 제안한 것이다.