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양일호,정진우,허명,김영신,김진수,김민경,최현동,오창호,Yang Il-Ho,Jeong Jin-Woo,Hur Myung,Kim Young-Shin,Kim Jin-Soo,Kim Min-Kyung,Choi Hyun-Dong,Oh Chang-Ho 한국초등과학교육학회 2005 초등과학교육 Vol.24 No.5
The purpose of this study was to develop an instrument for analysing elementary secondary school, and university science laboratory instructions. The categories of this analysis instrument were instituted through literature overviews and interactions with three researchers in a science classroom analyst team, a doctoral student, and eight master level students, who participated in the process of modification of the analysis instruments on the science laboratory instructions. The contents areas were divided into three categories: aims of laboratory activities, interactions, and scientific inquiry processes. Each category contains $2\~3$ items. So the instrument consisted of 20 subcategories. The validity of the this instrument was achieved through checking with 4 science education specialists.
초등학교 신규교사의 과학수업에서 나타나는 수업기술의 특징
양일호,정진우,조현준,최현동,오창호,Yang Il-Ho,Jeong Jin-Woo,Cho Hyun-Jun,Choi Hyun-Dong,Oh Chang-Ho 한국초등과학교육학회 2005 초등과학교육 Vol.24 No.5
The purpose of this study was to investigate beginning elementary teachers' characteristics and improvement of their teaching skills in science class. The methodology of this study was a qualitative approach that included interviews, classroom observations, and teaching materials. In urban area, low beginning elementary teacher were selected. Four beginning elementary teachers were observed and recorded with VCR in their classroom at seven-times. The results showed that the beginning elementary teachers did not improve in their teaching skills in science teaching, and their characteristics of teaching skills in science were summarized as following; 1) their teaching methods were not inquiry-based science teaching, but explaining-based science teaching, 2) their main aims of the science teaching were focused on the science knowledges, 3) there were little students' science processes involved in their classes, 4) they focused on using textbook as teaching materials, 5) there were little waiting times after their questioning, and they usually used closed-questions rather than open-ended questions.
짧은 음성을 대상으로 하는 화자 확인을 위한 심층 신경망
양일호,허희수,윤성현,유하진,Yang, IL-Ho,Heo, Hee-Soo,Yoon, Sung-Hyun,Yu, Ha-Jin 한국음향학회 2016 韓國音響學會誌 Vol.35 No.6
본 논문에서는 짧은 테스트 발성에 대한 화자 확인 성능을 개선하는 방법을 제안한다. 테스트 발성의 길이가 짧을 경우 i-벡터/확률적 선형판별분석 기반 화자 확인 시스템의 성능이 하락한다. 제안한 방법은 짧은 발성으로부터 추출한 특징 벡터를 심층 신경망으로 변환하여 발성 길이에 따른 변이를 보상한다. 이 때, 학습시의 출력 레이블에 따라 세 종류의 심층 신경망 이용 방법을 제안한다. 각 신경망은 입력 받은 짧은 발성 특징에 대한 출력 결과와 원래의 긴 발성으로부터 추출한 특징과의 차이를 줄이도록 학습한다. NIST (National Institute of Standards Technology, 미국) 2008 SRE(Speaker Recognition Evaluation) 코퍼스의 short 2-10 s 조건 하에서 제안한 방법의 성능을 평가한다. 실험 결과 부류 내 분산 정규화 및 선형 판별 분석을 이용하는 기존 방법에 비해 최소 검출 비용이 감소하는 것을 확인하였다. 또한 짧은 발성 분산 정규화 기반 방법과도 성능을 비교하였다. We propose a method to improve the robustness of speaker verification on short test utterances. The accuracy of the state-of-the-art i-vector/probabilistic linear discriminant analysis systems can be degraded when testing utterance durations are short. The proposed method compensates for utterance variations of short test feature vectors using deep neural networks. We design three different types of DNN (Deep Neural Network) structures which are trained with different target output vectors. Each DNN is trained to minimize the discrepancy between the feed-forwarded output of a given short utterance feature and its original long utterance feature. We use short 2-10 s condition of the NIST (National Institute of Standards Technology, U.S.) 2008 SRE (Speaker Recognition Evaluation) corpus to evaluate the method. The experimental results show that the proposed method reduces the minimum detection cost relative to the baseline system.
커널 주성분 분석의 앙상블을 이용한 다양한 환경에서의 화자 식별
양일호,김민석,소병민,김명재,유하진,Yang, Il-Ho,Kim, Min-Seok,So, Byung-Min,Kim, Myung-Jae,Yu, Ha-Jin 한국음향학회 2012 韓國音響學會誌 Vol.31 No.3
본 논문에서는 커널 주성분 분석 (KPCA, kernel principal component analysis)으로 강화한 화자 특징을 이용하여 복수의 분류기를 학습하고 이를 앙상블 결합하는 화자 식별 방법을 제안한다. 이 때, 계산량과 메모리 요구량을 줄이기 위해 전체 화자 특징 벡터 중 일부를 랜덤 선택하여 커널 주성분 분석의 기저를 추정한다. 실험 결과, 제안한 방법이 그리디 커널 주성분 분석 (GKPCA, greedy kernel principal component analysis)보다 높은 화자 식별률을 보였다. In this paper, we propose a new approach to speaker identification technique which uses an ensemble of multiple classifiers (speaker identifiers). KPCA (kernel principal component analysis) enhances features for each classifier. To reduce the processing time and memory requirements, we select limited number of samples randomly which are used as estimation set for each KPCA basis. The experimental result shows that the proposed approach gives a higher identification accuracy than GKPCA (greedy kernel principal component analysis).
법음성학에서의 오디오 신호의 위변조 구간 자동 검출 방법 연구
양일호(Yang, IL-Ho),김경화(Kim, Kyung-Wha),김명재(Kim, Myung-Jae),백록선(Baek, Rock-Seon),허희수(Heo, Hee-Soo),유하진(Yu, Ha-Jin) 한국음성학회 2014 말소리와 음성과학 Vol.6 No.2
We propose a novel scheme for digital audio authentication of given audio files which are edited by inserting small audio segments from different environmental sources. The purpose of this research is to detect inserted sections from given audio files. We expect that the proposed method will assist human investigators by notifying suspected audio section which considered to be recorded or transmitted on different environments. GMM-UBM and GSV-SVM are applied for modeling the dominant environment of a given audio file. Four kinds of likelihood ratio based scores and SVM score are used to measure the likelihood for a dominant environment model. We also use an ensemble score which is a combination of the aforementioned five kinds of scores. In the experimental results, the proposed method shows the lowest average equal error rate when we use the ensemble score. Even when dominant environments were unknown, the proposed method gives a similar accuracy.