• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.449-456
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• 2004

This paper proposes a novel recognition model, a recurrent fuzzy associative memory(RFAM), for recognizing time-series patterns contained an ambiguity. RFAM is basically extended from FAM(Fuzzy Associative memory) by adding a recurrent layer which can be used to deal with sequential input patterns and to characterize their temporal relations. RFAM provides a Hebbian-style learning method which establishes the degree of association between input and output. The error back-propagation algorithm is also adopted to train the weights of the recurrent layer of RFAM. To evaluate the performance of the proposed model, we applied it to a word boundary detection problem of speech signal.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.12-18
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• 2011

Most smartphone use virtual keypads based on touch-pad. The virtual keypads often make typographical errors because of the physical limitations of device such as small screen and limited input methods. To resolve this problem, many similar word-finding methods have been studied. In the paper, we propose an edit distance method (a well-known string similarity measure) that is modified to consider various types of virtual keypads. The proposed method effectively covers typographical errors in various keypads by converting an input string into a physical key sequence and by reflecting characteristics of virtual keypads to edit scores. In the experiments with various keypads, the proposed method showed better performances than a typical edit distance method.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.90-98
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• 1996

In this paper we have proposed the sign language transformation system for deaf based on a morpheme analysis. The proposed system extracts phoneme components and connection informations of the input character sequence by using a morpheme analysis. And then the sign image obtained by component analysis is correctly and automatically generated through the sign image database. For the effective sign language transformation, the language description dictionary which consists of a morpheme analysis part for analysis of input character sequence and sign language description part for reference of sign language pattern is costructed. To avoid the duplicating sign language pattern, the pattern is classified a basic, a compound and a similar sign word. The computer simulation shows the usefulness of the proposed system.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.654-659
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• 2003

PVAP (Pressure Vessel Analysis Program V1.0) was developed by adopting the finite element analysis program ANSYS V6.0, and Microsoft Visual Basic V6.0 was also utilized for the interfacing and handling of input and output data during the analysis. PVAP offers the end user the ability to design and analyze vessels in strict accordance with ASME Section VIII, Division 2. More importantly, the user is not required to make any design decisions during the input of the vessel. PVAP consists of three analysis modules for the finite element analysis of the primary components of pressure vessel such as head, shell, nozzle, and skirt. In each module, finite element analysis can be performed automatically only if the end user gives the dimension of the vessel. Furthermore, the calculated results are compared and evaluated in accordance with the criteria given in ASME Boiler and Pressure Vessel Code, Section VIII, Division 2. In particular, heat transfer analysis and consecutive thermal stress analysis for the junction between skirt and head can be carried out automatically in the skirt-tohead module. Finally, report including the above results is created automatically in Microsoft Word format.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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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.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.79-88
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• 2007

As the mobile computers such as Personal Digital Assistants (PDAs) or Smart Phone has been widespread in our daily life, the demand of an extensive data input will gradually be increased. Consequently, many alternative soft keyboards have been proposed to satisfy this requirement. However none of them can provide an absolute solutions for that, the segregated guideline for keyboard arrangement and usage still cause much confusion to the user. Therefore, an integrated guideline is seriously required. In order to come up with the integrated guideline for Korean Soft keyboard GUI, the questionnaire and the experimental test compared with five soft keyboards were conducted in this study. As a result this paper presents five guidelines for improving an input speed of soft keyboard on the mobile computing; following familiarity for effective screen use, using a single key rather than grouping key, considering position of prediction word, considering prompt feedback, finally, considering optimized keyboard size.

• Smart Media Journal
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• v.7 no.2
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• pp.54-59
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• 2018

With the increasing use of touch-enabled mobile devices such as smartphones and tablet PCs, the works are done on desktop computers and smartphones, and tablet PCs perform laptops. However, due to the nature of smart devices that require portability, QWERTY keyboard is densely arranged in a small screen. This is the cause of different typographical errors when using the mechanical QWERTY keyboard. Unlike the mechanical QWERTY keyboard, which has enough space for each button, QWERTY keyboard on the touch screen often has a small area assigned to each button, so that it is often the case that the surrounding buttons are input rather than the button the user intends to press. In this paper, we propose a method to automatically correct the input errors of the QWERTY keyboard in the touch screen environment by using the n-gram language model using the word unigram and the bigram probability.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.81-89
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• 2021

This study proposes a text interface for support of language-based educational contents in a mobile platform environment. The proposed interface utilizes deep learning as an input structure to write words through handwriting. Based on GUI (Graphical User Interface) using buttons and menus of mobile platform contents and input methods such as screen touch, click, and drag, we design a text interface that can directly input and process handwriting from the user. It uses the EMNIST (Extended Modified National Institute of Standards and Technology database) dataset and a trained CNN (Convolutional Neural Network) to classify and combine alphabetic texts to complete words. Finally, we conduct experiments to analyze the learning support effect of the interface proposed by directly producing English word education contents and to compare satisfaction. We compared the ability to learn English words presented by users who have experienced the existing keypad-type interface and the proposed handwriting-based text interface in the same educational environment, and we analyzed the overall satisfaction in the process of writing words by manipulating the interface.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.4
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• pp.403-410
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• 2000

In this paper, the development of a stock information retrieval system using speech recognition and its features are described. The system is based on DHMM (discrete hidden Markov model) and PLUs (phonelike units) are used as the basic unit for recognition. End-point detection and echo cancellation are included to facilitate speech input. Continuous speech recognizer is implemented to allow multi-word speech. Data collected over several months are analyzed.

• ETRI Journal
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• v.30 no.1
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• pp.113-128
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• 2008

Turbo codes are extensively used in current communications standards and have a promising outlook for future generations. The advantages of software defined radio, especially dynamic reconfiguration, make it very attractive in this multi-standard scenario. However, the complex and power consuming implementation of the maximum a posteriori (MAP) algorithm, employed by turbo decoders, sets hurdles to this goal. This work introduces an ASIP architecture for the MAP algorithm, based on a dual-clustered VLIW processor. It displays the good performance of application specific designs along with the versatility of processors, which makes it compliant with leading edge standards. The machine deals with multi-operand instructions in an innovative way, the fetching and assertion of data is serialized and the addressing is automatized and transparent for the programmer. The performance-area trade-off of the proposed architecture achieves a throughput of 8 cycles per symbol with very low power dissipation.