• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.385-394
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• 2010

Automatic gain control(AGC) is used in hearing aids to compensate for the hearing level as to reduced dynamic range. AGC is consisted of the main 4 factors which are compression threshold, compression ratio, attack time, and release time. This study especially focus on each individual need for optimum release time parameters that can be changed within 7 certain range such as 12, 64, 128, 512, 2094, and 4096ms. To estimate the effect of various release time in AGC, twelve normal hearing and twelve hearing impaired listeners are participated. The stimuli are used by one syllable and sentence which have the same acoustic energy respectively. Then, each of score of the word recognition score is checked in quiet and noise conditions. As a result, it is verified that most people have the different best recognition score on specific release time. Also, if hearing aids is set by the optimum release time in each person, it is helpful in speech recognition and discrimination.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1043-1056
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• 2017

A styled document is a document that contains diverse decorating functions such as different font, colors, tables and images generally authored in a word processor (e.g., MS-WORD, Open Office). Compared to a plain-text document, a styled document enables a human to easily recognize a logical structure such as section, subsection and contents of a document. However, it is difficult for a computer to recognize the structure if a writer does not explicitly specify a type of an element by using the styling functions of a word processor. It is one of the obstacles to enhance document version management systems because they currently manage the document with a file as a unit, not the document elements as a management unit. This paper proposes a machine learning based approach to analyzing the logical structure of a styled document composing of sections, subsections and contents. We first suggest a feature vector for characterizing document elements from a styled document, composing of eight features such as font size, indentation and period, each of which is a frequently discovered item in a styled document. Then, we trained machine learning classifiers such as Random Forest and Support Vector Machine using the suggested feature vector. The trained classifiers are used to automatically identify logical structure of a styled document. Our experiment obtained 92.78% of precision and 94.02% of recall for analyzing the logical structure of 50 styled documents.

• MALSORI
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• no.35_36
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• pp.175-188
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• 1998

Database segmented and labeled up to phoneme level plays an important role in phonetic research and speech engineering. However, it usually requires manual segmentation and labeling, which is time-consuming and may also lead to inconsistent consequences. Automatic segmentation and labeling can be introduced to solve these problems. In this paper, we investigate a method to improve the performance of automatic segmentation and labeling system, where Spectral Variation Function(SVF), modification of silence model, and use of energy variations in postprocessing stage are considered. In this paper, SVF is applied in three ways: (1) addition to feature parameters, (2) postprocessing of phoneme boundaries, (3) restricting the Viterbi path so that the resulting phoneme boundaries may be located in frames around SVF peaks. In the postprocessing stage, positions with greatest energy variation during transitional period between silence and other phonemes were used to modify boundaries. In order to evaluate the performance of the system, we used 452 phonetically balanced word(PBW) database for training phoneme models and phonetically balanced sentence(PBS) database for testing. According to our experiments, 83.1% (6.2% improved) and 95.8% (0.9% improved) of phoneme boundaries were within 20ms and 40ms of the manually segmented boundaries, respectively.

• Korean Journal of Cognitive Science
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• v.23 no.1
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• pp.1-23
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• 2012

This study investigated the lexical access processing of inflected Korean verbs in the mental lexicon. In Korean, verbs can be classified into two main types of inflections, which are regular and irregular inflections, which can be further divided into three types of regular inflections and two types of irregular inflections. A masked priming lexical decision task was used and the priming effects were compared. Experiments were carried out using the five different types of verbal inflections in Korean: (1) No change-regularity (regular verbs with no orthographical or phonological changes), (2) Phonological change-regularity (regular verbs with phonological changes to the stem only), (3) Orthographical change-regularity (regular verbs that only undergo orthographical changes), (4) Stem change-irregularity (the stem is omitted or alternated with the other phoneme of the stem in irregular verbs), (5) Ending change-irregularity (irregular verbs with changes in the endings by phoneme substitution). The first three types are regarded as regular verbal inflections whereas the latter two types are regarded as irregular verbal inflections. The infinitive forms of the verb were presented as target words and three different conditions were presented as prime words. The three conditions included regular verbal inflection, irregular verbal inflection, and a control condition in which morphologically and semantically unrelated primes were presented. In addition, different stimulus onset asynchrony (SOA) were manipulated (43ms, 72ms, 230ms) to examine the time frame of the morphological decomposition process in word recognition. The results revealed that there were significant priming effects in all three SOAs across conditions. Hence, there was no significant differences in priming effects between regular and irregular verbal inflection conditions. This may suggest that Korean verb processing does not adopt different processing routes for regular and irregular inflections, which can also be an indication of earlier morphological information processing for Korean verbs.

• Korean Journal of Cognitive Science
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• v.6 no.2
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• pp.97-116
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• 1995

This study was conducted to investigate how syntaction and pragmatic constraints influence the sentential representation and memory accessibility. In order to seperate the syntactic constraints from the pragmatic constraint from the pragmatic constraints,the syntactic role of constituent in the sentence (subject or object) and the order of mention(first or second) were manipulted.After each sentence was presented by RSVP procedure,the probe recognition time was measured to investigate memory accessibility.In Experiment 1,in which SOA interval was 255ms,it was found that the subject of a sentece were more accessible than the object and participants first in a sentence were more accessible than participants mentioned later.However, in Experiment 2,in which SOA interval was 1540ms,it was found that participants mentioned first in a sentence were more accessible than participants mentioned later while there was no significant difference between the subject and object of a sentece.These results suggest that the syntactic and pragmatic constraints have an independent effect on the initial senential representation at the early stage of constructing representation,but as time passes only the pragmatic constraints influence sentential representation.These results also support a theoretical position which assumes that sentential representation is constructed through the process of convergent statisfaction of multiple constraints.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.509-512
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• 2001

본 논문은 한국어 음성에 대한 한국어 단어의 음소단위 분할을 목적으로 하였다. 대상 단어는 원광대학교 phonetic balanced 452단어 데이터 베이스를 사용하였고 분할 단위는 음성 전문가에 의해 구성된 44개의 음소셋을 사용하였다. 음소를 분할하기 위해 음성을 각각 프레임으로 나눈 후 각 프레임간의 스펙트럼 성분의 유사도를 측정한 후 측정한 유사도를 기준으로 음소의 분할점을 찾았다. 두 프레임 간의 유사도를 결정하기 위해 두 벡터 상호간의 유사성을 결정하는 방법중의 하나인 Lukasiewicz implication을 사용하였다. 본 실험에서는 기존의 프레임간 스펙트럼 성분의 유사도 측정을 이용한 하나의 어절의 유/무성음 분할 방법을 본 실험의 목적인 한국어 단어의 음소 분할 실험에 맞도록 수정하였다. 성능평가를 위해 음성 전문가에 의해 손으로 분할된 데이터와 본 실험을 통해 얻은 데이터와의 비교를 하여 평가를 하였다. 실험결과 전문가가 직접 손으로 분할한 데이터와 비교하여 32ms이내로 분할된 비율이 최고 84.76%를 나타내었다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.131-135
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• 2000

본 논문에서는 고성능 고정 소수점 DSP (Digital Signal Processor) 코어인 Vincent6 코어 [1]를 이용하여 ITU-T C.728 음성 부호화기를 실시간으로 구현하였다 G.728 은 16 kb/s전송률의 ITU-T표준 음성 부호화기이며, 입력신호는 8 kHz로 샘플링되며 샘플 당 16 bit 로 양자화된 PCM 신호이다. G.728 은 LD-CELP(Low Delay Code Excited Linear Prediction)라고도 하며, 알고리 듬 delay는 0.625ms 이다. Vincent6 DSP core 는 VLIW (Very-Long Instruction Word) 특성을 가지므로 다중 명령 (multiple instruction)을 수행할 수 있다 이를 위해서 G.728 annex G를 이용하여 고정 소숫점 연산으로 코드를 작성한 후, 이를 vincent6 어셈블리 코드로 구현하였다. 최종적으로 구현된 코드는 ITU-T 의 test vector 에 대 해 bit exact 한 결과를 보이며 34 MCPS (Million Cycles Per Second)의 계산량을 가지며 사용 메모리크기는 데이터 메모리가 약 9KByte, 프로그램 메모리가 약 57 KByte 이다.

• Speech Sciences
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• v.9 no.3
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• pp.169-184
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• 2002

Korean has two types of voiceless alveolar fricatives: a non-tense fricative /$S^{h}$ and a tense fricative /s'/. Twenty native speakers of Korean produced five pairs of isolated words containing word initial $S^{h}V$ and /s'V/ sequences where V was any one of five (/a, e, i, o, u/) of Korean vowels. Acoustic measures such as duration, fricative noise prominent frequency, energy change of following vowel, and fundamental frequency at vowel onset were examined. Results showed that among the parameters, aspiration noise duration of /s'/ in mid and low vowel contexts was less than 21 ms. In a perception experiment, where only the aspiration noise interval of the /$S^{h}$/ tokens was incrementally reduced, some listeners shifted perception from /$S^{h}$/ to /s'/.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.462-465
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• 2000

최근 많은 양의 문서가 전자화되어 컴퓨터에 저장되고 인터넷을 통하여 공유가 되고 있고, 그 범위를 고문헌에까지 넓혀가고 있다. 그러나 한자 문화권의 고문헌은 대부분 2만에서 3만여자의 한자로 작섣되어 있어서 한자 입력시 코드문제가 뒤따른다. 하지만 유니코드 3.0에서는 27,786자의 한자를 코드화 하여 놓아서 한자 문화권 나라에 많은 도움을 주고 있다. 하지만 한중일 3개국에서 많이 쓰이는 한자를 대상으로 하여 부수, 획수 순으로 정렬하여 국내 실정에 맞지 않고 그나마 유니코드 한자를 입력할 수 있는 환경도 MS Word 2000 정도로 제한적이다. 본 논문에서는 유니코드 3.0 한자 입력기에서 기본 한자 코드로 상요될 CJK 한자 영역에 배정된 한자를 정렬하는 방안을 제안하고 운영체제 독립적인 한자 입력 시스템에 활용한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.553-558
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• 2001

종이책의 디지털 형태인 전자책은 종이책에 비해 인쇄와 유통, 저장 관리가 효율적이고, 인터랙티브한 멀티미디어 정보 표현 등이 가능한 장점을 지니고 있기 때문에 향후 시장이 급성장할 것으로 예측되며, 현재 전자책 시장의 선결 조건인 전자책 문서 표준 및 저작권, 단말기의 해상도 문제 등이 하나씩 해결되어 가고 있다. 그러나 아직까지 전자책의 활성화를 위한 전자책 컨텐츠의 숫자가 많이 부족한 현실이다. 이에 본 연구에서는 전자책 컨텐츠를 확대하기 위하여 기존의 종이책으로 작성된 저작물을 전자책으로 변환하는 기법에 대해 연구한다. 특히 기존 종이책을 저작하는 문서 도구 중에서 가장 대중적이고 사용하기 쉬운 HWP문서와 EBKS 전자책 문서 표준간의 변환 기법에 대해 연구한다. 이 변환 기법은 단순히 HWP 환경에서만 적용가능한 것이 아니라 Quark이나 MS-WORD등의 다른 문서 저작도구에서도 사용가능한 일반적인 방법이다.