• 대한산업공학회지
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• 제42권4호
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• pp.280-289
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• 2016

User authentication is an important issue on computer network systems. Most of the current computer network systems use the ID-password string match as the primary user authentication method. However, in password-based authentication, whoever acquires the password of a valid user can access the system without any restrictions. In this paper, we present a keystroke dynamics-based user authentication to resolve limitations of the password-based authentication. Since most previous studies employed a fixed-length text as an input data, we aims at enhancing the authentication performance by combining four different variable creation methods from a variable-length free text as an input data. As authentication algorithms, four one-class classifiers are employed. We verify the proposed approach through an experiment based on actual keystroke data collected from 100 participants who provided more than 17,000 keystrokes for both Korean and English. The experimental results show that our proposed method significantly improve the authentication performance compared to the existing approaches.

• 한국항행학회논문지
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• 제19권5호
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• pp.452-457
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• 2015

최근 사용자들의 취향을 고려하는 다양한 디자인을 내세워 기존의 안경, 시계 등의 친숙한 형태의 웨어러블 디바이스가 등장하면서 많은 인기를 얻고 있다. 하지만 착용이 가능한 초소형 디바이스라는 특성을 고려하지 않고 기존의 스마트폰 UI/UX를 적용하였기 때문에 작은 디스플레이 상에서 문자 입력이라는 문제점을 안고 있다. 이에 본 논문에서는 스마트워치와 같은 웨어러블 디바이스의 기존 입력 방법과 관련 연구들을 분석하여 UI/UX에 대한 문제점을 도출하고 스마트 워치를 위한 새로운 입력 방식을 제안한다. 이를 위해, 트랙볼 센서를 활용하여 웨어러블 디바이스에서 효율적인 문자 입력이 가능하도록 설계하고 구현한 결과를 통해 제안된 인터페이스의 유용성 및 성능을 검증한다.

• Journal of Information Processing Systems
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• 제4권2호
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• pp.77-86
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• 2008

This research proposes a new neural network for text categorization which uses alternative representations of documents to numerical vectors. Since the proposed neural network is intended originally only for text categorization, it is called NTC (Neural Text Categorizer) in this research. Numerical vectors representing documents for tasks of text mining have inherently two main problems: huge dimensionality and sparse distribution. Although many various feature selection methods are developed to address the first problem, the reduced dimension remains still large. If the dimension is reduced excessively by a feature selection method, robustness of text categorization is degraded. Even if SVM (Support Vector Machine) is tolerable to huge dimensionality, it is not so to the second problem. The goal of this research is to address the two problems at same time by proposing a new representation of documents and a new neural network using the representation for its input vector.

• 스마트미디어저널
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• 제4권3호
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• pp.44-49
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• 2015

Text line segmentation is a preprocessing step in OCR, which can significantly influence the accuracy of document analysis applications. This paper proposes a novel methodology for the text line segmentation of handwritten documents. First, the average width of the connected components is used to form a 1-D Gaussian kernel and a smoothing operation is then applied to the input binary image. The adaptive binarization of the smoothed image forms the final text lines. In this work, the segmentation method involves two stages: firstly, the large connected components are labelled as a unique text line using text line area mapping. Secondly, the final refinement of the segmentation is performed using the Euclidean distance between the text line and small connected components. The group of uniquely labelled text candidates achieves promising segmentation results. The proposed approach works well on Korean and English language handwritten documents captured using a camera.

• 한국디자인학회:학술대회논문집
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• 한국디자인학회 2005년도 춘계 학술발표대회 논문집
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• pp.204-205
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• 2005

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.51.5-51
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• 2002

In this paper, we propose and developed a keyglove using the touch-typing method as new solutions to the problem of text input into the mobile computing devices. This device recognizes that character is typed in though the hand's movements analysis and requires no additional space on a person's desktop or work surface, and can be easily used with computers of any size, even the smallest mobile computer, and is designed as an input device for wearable computers and virtual environment. The concept of the wearable input device based on human hand-molies recognition.

• 말소리와 음성과학
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• 제10권1호
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• pp.39-48
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• 2018

A typical statistical parametric speech synthesis (text-to-speech, TTS) system consists of separate modules, such as a text analysis module, an acoustic modeling module, and a speech synthesis module. This causes two problems: 1) expert knowledge of each module is required, and 2) errors generated in each module accumulate passing through each module. An end-to-end TTS system could avoid such problems by synthesizing voice signals directly from an input string. In this study, we implemented an end-to-end Korean TTS system using Google's Tacotron, which is an end-to-end TTS system based on a sequence-to-sequence model with attention mechanism. We used 4392 utterances spoken by a Korean female speaker, an amount that corresponds to 37% of the dataset Google used for training Tacotron. Our system obtained mean opinion score (MOS) 2.98 and degradation mean opinion score (DMOS) 3.25. We will discuss the factors which affected training of the system. Experiments demonstrate that the post-processing network needs to be designed considering output language and input characters and that according to the amount of training data, the maximum value of n for n-grams modeled by the encoder should be small enough.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 2007년도 정기학술대회
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• pp.405-414
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• 2007

This paper describes a preliminary work on prosody modeling aspect of a text-to-speech system for Thai. Specifically, the model is designed to predict symbolic markers from text (i.e., prosodic phrase boundaries, accent, and intonation boundaries), and then using these markers to generate pitch, intensity, and durational patterns for the synthesis module of the system. In this paper, a novel method for annotating the prosodic structure of Thai sentences based on dependency representation of syntax is presented. The goal of the annotation process is to predict from text the rhythm of the input sentence when spoken according to its intended meaning. The encoding of the prosodic structure is established by minimizing speech disrhythmy while maintaining the congruency with syntax. That is, each word in the sentence is assigned a prosodic feature called strength dynamic which is based on the dependency representation of syntax. The strength dynamics assigned are then used to obtain rhythmic groupings in terms of a phonological unit called foot. Finally, the foot structure is used to predict the durational pattern of the input sentence. The aforementioned process has been tested on a set of ambiguous sentences, which represents various structural ambiguities involving five types of compounds in Thai.

• 대한인간공학회지
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• 제31권4호
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• pp.493-498
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• 2012

Objective: The purpose of this study is to suggest the hierarchical structure with three layers of input task, input interaction, and input device. Background: Understanding the input interaction is very helpful to design an interface design. Method: We made a model of three layered input structure based on empirical approach and applied to a gesture interaction in TV. Result: We categorized the input tasks into six elementary tasks which are select, position, orient, text, and quantify. The five interactions described in this paper could accomplish the full range of input interaction, although the criteria for classification were not consistent. We analyzed the Microsoft kinect with this structure. Conclusion: The input interactions of command, 4 way, cursor, touch, and intelligence are basic interaction structure to understanding input system. Application: It is expected the model can be used to design a new input interaction and user interface.

• 한국음향학회지
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• 제22권8호
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• pp.703-710
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• 2003

코퍼스 기반 음성합성방식은 그 합성음의 자연성이 매우 우수하여 널리 사용되고 있으나 대용량의 데이터베이스 (DB)를 사용하기 때문에 그 적용분야가 매우 제한적이다. 본 연구에서는 이러한 코퍼스 기반 음성합성기의 대용량 DB 문제를 해결하기 위한 방안으로서 DB 축소 방법 대한 알고리듬을 제안하고 평가하였다. 본 논문에서는 DB 축소 알고리듬으로서 세 가지 방법을 제안하였는데, 첫 번째는 Modified K-means 군집화를 이용한 DB 축소 알고리듬이고 다음은 적절한 문장 셋을 정의하고 이 문장 셋을 합성할 때 사용된 단위들을 이용하는 방법이다. 마지막으로는 대용량 문장 셋을 정의하고 해당 문장을 음성합성하고, 음편들의 사용 빈도수를 고려하여 군집화를 하는 것이다. 세 가지 방법을 이용하여 합성 DB를 유사한 크기로 축소하였을 때, 대용량 문장 셋과 빈도를 고려한 세 번째 방법이 가장 우수한 음질을 보였다. 또한 마지막 방법은 합성음의 음질은 저하시키지 않으면서 합성 DB만을 감소시키는 성능을 보여, 제안된 방법의 타당함을 입증할 수 있었다.