• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.267-278
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• 2017

As the same letter can be pronounced differently depending on word contexts, one should refer to a lexicon in order to pronounce a word correctly. Phonetic alphabets that lexicons adopt as well as pronunciations that lexicons describe for the same word can be different from lexicon to lexicon. In this paper, we use a sequence-to-sequence model that is widely used in deep learning research area in order to convert automatically from one pronunciation to another. The 12 seq2seq models are implemented based on pronunciation training data collected from 4 different lexicons. The exact accuracy of the models ranges from 74.5% to 89.6%. The aim of this study is the following two things. One is to comprehend a property of phonetic alphabets and pronunciations used in various lexicons. The other is to understand characteristics of seq2seq models by analyzing an error.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.814-820
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• 2009

The arrangement of the general 12-button cellular phone keypad is unified with one or two kind. In general, the several alphabets are arranged in one key. When inputting an English, countries which do not speak English use multi-tap method. We can input next alphabet by pressing key repeatedly. We address the problem of finding multi-tap-based keypad designs which minimize the number of key presses for various case. Genetic algorithms is proposed method for optimal keypad designs. We are to maintain the number of keys, which is ranged from 8 to 12. We also show experimental using non-alphabetically-constrained and alphabetically-constrained arrangement, respectively. Finally, we give improved keypad designs.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1983.04a
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• pp.18-28
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• 1983

This paper describes the result of a series of fundamental researches on a word processing system, named WORD80. Given the text consisting of Ilanguel characters, Chinese characters, English alphabets and other special characters, it can provide-ㄴo-see printout, after having processed according to the commands used to control the output format of the text. Since each Hanguel character in input text is made up of and is represented as some compoents, it uses the deterministic finite automata for the formation of Hanguel from its components. When developed at first, the WORD80 can perform Hanguel to Chinese transition character by character by character. But it was thought to be more practical to do this word by word.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.913-916
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• 1998

In this paper, to provide the robustness of character recognition, we propose a recognition method using the dilated boundary curve feature which has the invariance characteristics for the shift, scale, and rotation changes of character pattern. And its some characteristics and effectieness are evaluated through the experiments for both the english alphabets and the numeral digits. The feature vector is represented by the fourier descriptor for a boundary curve of the dilated character pattern which is generated by the circular mask dilation method, and is used for a nearest neighbort classifier(NNC) or a nearest neighbor mean classifier(NNMC). These the processing time and the recognition rate, and take also the robustness of recognition for both some internal noise and partial corruption of an image pattern.

• Journal of The Korean Association of Information Education
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• v.2 no.1
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• pp.138-161
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• 1998

This research addresses to establish a systematic approach to design a standard Hangul code system for educational purposes in development of CAI courseware using Korean, English, and Chinese characters, which requires data exchanges and database construction. In this paper, types of Korean alphabetic code systems already in use, their representational environments and consonant/vowel order have been studied and analysed. This paper presents the requirements that the hangul code system for educational purpose needs to obtain. First, it should be able to represent all contemporary as well as ancient Korean alphabets. Second, character elements should be separable. Third, consonant/vowel order should be determined to easily retrieve and exchange data. Lastly, the code should maintain compatibility with other national codes and provide uniqueness of user-defined character codes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.134-140
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• 1994

In this paper, an algorithm of CBAM(Combination Bidirectional Associative Memory) model proposes, analyzes and tests CBAM model `s performancess by simulating with recalls and recognitions of patterns. In learning-procedure each correlation matrix of training patterns is obtained. As each correlation matrix's some elements correspond to juxtaposition, all correlation matrices are merged into one matrix (Combination Correlation Matrix, CCM). In recall-procedure, CCM is decomposed into a number of correlation matrices by spiliting its elements into the number of elements corresponding to all training patterns. Recalled patterns are obtained by multiplying input pattern with all correlation matrices and selecting a pattern which has the smallest value of energy function. By using a CBAM model, we have some advantages. First, all pattern having less than 20% of noise can be recalled. Second, memory capacity of CBAM model, can be further increased to include English alphabets or patterns. Third, learning time of CBAM model can be reduced greatly because of operation to make CCM.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.43-56
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• 2010

Completely Automated Public Turing test to tell Computers and Humans Apart or CAPTCHA has received remarkable attention. Deciphering distorted texts is still a human task. The current CAPTCHA mainly requires users to read English alphabets. As such, Thai CAPTCHA may be the choice for Thai online practitioners. However, no published work has examined how Thai online practitioners perceive CAPTCHA. This study thus attempts to fill this void. Based on the 112 number of usable online questionnaire submission, Thai online practitioners are all aware of CAPTCHA. Also, nine out of ten samples identified correctly the prime benefits of CAPTCHA. Using exploratory factor analysis, their attitude towards CAPTCHA was classified into two dimensions. They perceived (1) drawback of general CAPTCHA and (2) feasibility of Thai CAPTCHA. In addition to extending our insight into application of CAPTCHA, policy-makers responsible for electronic commerce in Thailand could initiate plans in response to Thai online practitioners' perception.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.435-436
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• 2007

Although previous speech analysis programs usually provide speech analysis and phoneme labeling functionalities, they require much time in manual labeling and support only English alphabets. To solve these problems, we develop a new Windows-based program with an improved phoneme and tone labeling method as well as the conventional speech analysis functionalities. The developed program has the unique feature in semi-automatic phoneme and tone labeling based on hidden Markov models.

• Korean Journal of Cognitive Science
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• v.9 no.1
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• pp.1-11
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• 1998

In this paper, the features which are thought to be used by humans based on the psychological experiment of human information processing are applied to character recognition problem. Man will deal with a little large area information as well as pixel by pixel information. Therefore we define the feature that represents a little wide region I information called region feature, and combine the features derived from region feature and pixel by pixel features that have been used by now. The features we used are the result of region feature based preanalysis, mesh with region attributes, cross distance difference and gradient. The training and test data in the experiment are handwritten Korean alphabets, digits and English alphabets, which are trained on neural network using back propagation algorithm and recognition results are 90.27-93.25%, 98.00% and 79.73-85.75%, respectively Experimental results show that the feature we are suggesting in this paper is 1-2% better than UDLRH feature similar in attribute to region feature, and the tendency of misrecognition is more easily acceptable by humans.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.2
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• pp.157-168
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• 1993

In this paper, it is shown that neural networks trained with back propagation algorithm and dictionary can be applied to recognize handwritten English characters. To eliminate the useless data part and to minimize the variety of characters from the scanned image file, various preprocessings : that is, segmentation, centering, noise filtering, sealing and thinning are performed. After these, characteristic features are derived from thinned character pattern. The neural network is trained by using the extracted features for sample data, and all test data are classified into English alphabets according to their features through the neural network. Finally, the ways of reducing learning time and improving recognition rate, and the relationship between learning time and hidden layer nodes are considered. As a result of this study, after successful training, a high recognition rate has been obtained with this system for the trained patterns and about 93% for test patterns. Using dictionary, the recognition rate was about 97% for test pattern.