• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1541-1547
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• 1988

In this paper, a new model for isolated word recognition called segment probability model is proposed. The proposed model is composed of two procedures of segmentation and modelling each segment. Therefore the spoken word is devided into arbitrary segments and observation probability in each segments is obtained using vector quantization. The proposed model is compared with pattern matching method and hidden Markov model by recognition experiment. The experimental results show that the proposed model is better than exsisting methods in terms of recognition rate and caculation amounts.

• Journal of Computing Science and Engineering
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• v.10 no.4
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• pp.103-110
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• 2016

Emotion recognition is an important component of affective computing, and is significant in the implementation of natural and friendly human-computer interaction. An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem. However, in emotion recognition, the texts involved are usually very short, leaving a very large, sparse feature space, which decreases the performance of emotion classification. This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster features, offering a novel word clustering algorithm, and using a new feature weighting scheme. Emotion classification experiments were performed with different features and weighting schemes on a publicly available dataset. The experimental results suggest that the word cluster features and the proposed weighting scheme can partly resolve problems with feature sparseness and emotion recognition performance.

• Speech Sciences
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• v.11 no.3
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• pp.111-128
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• 2004

In English, a focused word with new information receives a pitch accent. This paper examines how English native speakers and Korean speakers produce and perceive focus in English yes-no questions. The production experiments show that native speakers realize an appropriate intonation of yes-no questions, in which a focused word has a low pitch accent followed by a high phrasal accent and a high boundary tone. However, Korean speakers usually give a high tone to a focused word. In a like manner, the perception experiments show that English native speakers judge a word with a low tone to be focused, while Korean speakers have difficulty in comprehending a focused word realized as a low tone. And it is found that Korean speakers tend to perceive low tones on sentence initial and final focused words better than those on sentence medial focused words, and they often perceive a word with a relatively high fundamental frequency or a sharp rise of fundamental frequency as a focused word. This paper shows that Korean speakers have trouble to produce and perceive an appropriate tonal pattern of a focused yes-no question, and that can cause confusion in a conversation with native speakers.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.200-207
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• 2001

In this paper, we propose an HMM(Hidden Markov modeJ)-MLP(Multi-layer perceptron) hybrid model for recognizing legal words on the English bank check. We adopt an explicit segmentation-based word level architecture to implement an HMM engine with nonscaled and non-normalized symbol vectors. We also introduce an MLP for implicit segmentation-based word recognition. The final recognition model consists of a hybrid combination of the HMM and MLP with a new hybrid probability measure. The main contributions of this model are a novel design of the segmentation-based variable length HMMs and an efficient method of combining two heterogeneous recognition engines. ExperimenLs have been conducted using the legal word database of CENPARMI with encouraging results.

• Journal of the Korean Mathematical Society
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• v.59 no.1
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• pp.1-12
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• 2022

We introduce the notion of a minimal synchronizing word; that is a synchronizing word whose proper subwords are not synchronized. This has been used to give a new shorter proof for a theorem in [6]. Also, the common synchronized components of a subshift and its derived set have been characterized.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.376-379
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• 2018

본 논문의 목적은 오픈 소스로 공개된 3가지 한국어 형태소 분석기 (kkma, twitter 및 mecab-ko)를 비교해서 한국어 자연어 처리에 가장 적합한 분석기를 선정하는 것이다. 이를 위해, 자연어 처리 분야에서 중요한 단어 임베딩 방법론 중 하나인 word2vec 모델의 성능 검증 방법을 사용해서 각 형태소 분석기의 성능을 정량적으로 비교했다. 그 결과 mecab-ko 형태소 분석기가 최적임이 확인되었다. 단 성능 검증에 사용된 어휘가 오직 명사뿐이라는 한계가 있으므로, 향후 연구에서는 좀 더 다양한 품사에 대한 성능검증이 필요할 것으로 보인다.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.159-175
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• 2010

In this paper we make a new problem solving model using the principle of the lever. Using the model we solved many word problems related with consistency. We suggest new problem solving method using the lever model and describe some characteristics of the method.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.199-206
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• 2003

one of the representative micropayment protocols. The original PayWord system is designed for a user who generates paywords by performing hash chain operation for payment to an only designated vendor. In other words, a user has to create new hash chain values in order to establish commercial transactions with different vendors on the Internet. Therefore, we suggest an efficient scheme that is able to deal with business to different vendors by using only one hash chain operation to supplement this drawback. In this proposed system, a broker creates a new series of hash chain values along with a certificate for the user's certificate request. This certificate is signed by a broker to give authority enabling a user to generate hash chain values. hew hash chain values generated by a broker provide means to a user to do business with multiple vendors.

• Journal of the Korean Society for Library and Information Science
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• v.34 no.1
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• pp.229-242
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• 2000

Today, we are confronted with huge amount of data which contain complex documents, images and multimedia contents. Therefore a new method is needed to analyze and manage the mathematical expressions and extract new Information from them. It is more and more important to manage the document files including mathematical expressions which are generated by general-purpose word processors. Three major word processors are shared over 90% of domestic market. These are HWP, TeX and MS word. Due to the progress of Internet and digital library, it is necessary to develop a system to manage the document file containing mathematical expressions over the Web.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1716-1725
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• 1996

In this paper, the huffman decoder which is a part of the decoder in JPEG standard format is designed by using a new Ternary CAM. First, the 256 word * 16 bit-size new bit-word all parallel Ternary CAM system is designed and verified using SPICE and CADENCE Verilog-XL, and then the verified novel Ternary CAM is applied to the new huffman decoder architecture of JPEG. So the performnce of the designed CAM cell and it's block is verified. The new Ternary CAM has various applications because it has search data mask and storing data mask function, which enable bit-wise search and don't care state storing. When the CAM is used for huffman look-up table in huffman decoder, the CAM is partitioned according to the decoding symbol frequency. The scheme of partitioning CAM for huffman table overcomes the drawbacks of all-parallel CAM with much power and load. So operation speed and power consumption are improved.