• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.267-274
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• 2021

The purpose of this study is to investigate differences in learning flow and teaching presence according to the lecturer's appearance and the lecturer's speech rate. For this experiment, 183 freshman students from Xingtai University in China were selected as subjects of the experiment, and a total of four types of lecture videos were developed to test the lecturer's appearance and their speech rates. Data was analyzed through multivariate analysis of variance. According to the results of the analysis, first, learning flow and teaching presence of groups who experienced the presence of the lecturer appeared were significantly higher than the groups who learned without the appearance of the lecturer. Second, the groups who learned from videos with a fast speech rate showed higher learning flow and teaching presence than the group who learned at a slow speech rate. Third, there were no significant differences in both learning flow and teaching presence according to the lecturer's appearance and speech rate. This result provides a theoretical and practical basis for developing customized videos according to learners' characteristics.

• Phonetics and Speech Sciences
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• v.14 no.1
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• pp.21-28
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• 2022

Previous studies have provided important findings on children's speech production development. They have revealed that essentially all aspects of children's speech shift toward adult-like characteristics over time. Nevertheless, few studies have examined the perceptual aspects of children's speech tokens, as perceived by naive adult listeners. To fill the gap between children's production and adults' perception, we conducted cross-sectional perceptual studies of monosyllabic words produced by children aged two to six years. Monosyllabic words in the consonant-vowel-consonant form were extracted from children's speech samples and presented aurally to five listener groups (20 listeners in total). Generally, the agreement rate between children's production of target words and adult listeners' responses increases with age. The perceptual responses to tokens produced by two-year old children induced the largest discrepancies and the responses to words produced by six years olds agreed the most. Further analyses were conducted to identify the sources of disagreement, including the types of segments and syllable structure. This study makes an important contribution to our understanding of the development and perception of children's speech across age groups.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.351-354
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• 1999

본고는 현대 러시아어 이중자음1의 장단 발음 경향을 연구하는 과정에서 채택된 실험음성학적 방법론을 상술하는 것을 목적으로 하며, 자연 발화에서의 자음의 상대적 길이를 설정하는 문제와, 그 상대적 길이를 고려하여 자음의 장단을 결정하는 문제를 다룬다. 자음의 상대적 길이는 해당 이중자음과 그 자음을 둘러싼 모음 전체의 길이에 대한 해당 자음의 길이의 비율을 백분율로 환산한 것으로 설정한다. 그 상대적 길이의 관점에서 자음의 장단 결정을 위한 기준을 마련하기 위하여 러시아어 자음의 장단 인지에 관한 실험을 실시하였으며, 그 결과 이중자음의 장단음 구별 불가 구간을 설정하였고, 그것을 자음의 장단 결정에서 기준으로 사용하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.135-140
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• 2009

본 논문은 한국어 8 단모음을 인식하는 자동 독화 신경망 시스템을 구축한 것이다. 얼굴의 특정들은 휘도와 채도 성분으로 인하여 다양한 색 공간에서 다양한 표현 값을 갖는다. 이를 이용하여 각 표현 값들을 증폭하거나 축소, 대비시킴으로서 얼굴 특정들을 추출되게 하였다. 눈과 코, 안쪽 입의 외곽선, 이의 외곽선을 찾았고, 그 후 한국어 8모음 발화시 구분되게 변화는 값들을 파라미터로 설정하였다. 한국어 8모음을 발화하는 2400개의 자료를 모아 분석하고 이 분석을 바탕으로 신경망 시스템을 구축하여 실험하였다. 이 실험에 정상인 5명이 동원되었고, 사람들 사이에 있는 관찰 오차를 정규화를 통하여 수정하였다. 5명으로 분석하였고, 5명으로 인식 실험하여 좋은 결과를 얻었다.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.56-59
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• 2017

CNN(Convolutional Neural Network)을 이용하여 발화 주제 다중 분류 task를 multi-labeling 방법과, cluster 방법을 이용하여 수행하고, 각 방법론에 MSE(Mean Square Error), softmax cross-entropy, sigmoid cross-entropy를 적용하여 성능을 평가하였다. Network는 음절 단위로 tokenize하고, 품사정보를 각 token의 추가한 sequence와, Naver DB를 통하여 얻은 named entity 정보를 입력으로 사용한다. 실험결과 cluster 방법으로 문제를 변형하고, sigmoid를 output layer의 activation function으로 사용하고 cross entropy cost function을 이용하여 network를 학습시켰을 때 F1 0.9873으로 가장 좋은 성능을 보였다.

• Proceedings of the KSLP Conference
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• 1993.12a
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• pp.11-11
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• 1993

현존하는 문헌에 의하면, 입술근육의 수축과 운동시간의 측면에서 영어의 자음을 경음-연음분류를 할 수 있는 음성학적 실증이 없는 것으로 나타나고 있다. 본 연구는 근육운동 측정기를 사용하여 영어와 한국어의 양순 정지음의 발화시 근육(orbicularis oris superior muscle)운동을 측정하였다. 영어의 강세음절에서는 기존의 주장과 같이 /p/와 /b/의 발화시 근육운동에 차이가 없거나 일관성이 없는 것으로 나타났으나, 무강세음절에는 기존 이론과 달리 근육운동수축에 있어서 /p/가 /b/에 비하여 통계학적으로 훨씬 큰 것으로 나타났다.(중략)

• 방재와보험
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• s.150
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• pp.36-41
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• 2013

• Fire Protection Technology
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• s.54
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• pp.10-13
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• 2013

• Fire Science and Engineering
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• v.25 no.3
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• pp.63-71
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• 2011

In this study, it was evaluated the fire risk of an electric heater as representative seasonal appliances. Two type of electric heaters were used in experiments. When electric heaters were operated, temperature variation was measured around the heater. Internal structure was understood by Nondestructive inspection. It was evaluated the tire risk of electric heaters, when flammable materials were positioned ear a heater. It was also estimated the probability of a tire in case of malfunction of a safety tip-over witch. When a heater was operated in a normal condition, temperature was maintained under $80^{\circ}C$ around the heater. The possibility of a fire is very high, when a heater is covered with flammable materials or malfunction of safety parts (safety tip-over switch, anti-overheating devices).

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.59-66
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• 2008

This paper describes a novel method for identifying the main topic and detecting topic changes in a text-based dialogue as in Instant Messaging (IM). Compared to other forms of text, dialogues are uniquely characterized with the short length of text with small number of words, two or more participants, and existence of a history that affects the current utterance. Noting the characteristics, our method detects the main topic of a dialogue by considering the keywords not only the utterances of the user but also the dialogue system's responses. Dialogue histories are also considered in the detection process to increase accuracy. For topic change detection, the similarity between the former utterance's topic and the current utterance's topic is calculated. If the similarity is smaller than a certain threshold, our system judges that the topic has been changed from the current utterance. We obtained 88.2% and 87.4% accuracy in topic detection and topic change detection, respectively.