• Smart Media Journal
• /
• v.12 no.2
• /
• pp.56-65
• /
• 2023

In broadcasts such as news and coverage programs, voice is modulated to protect the identity of the informant. Adjusting the pitch is commonly used voice modulation method, which allows easy voice restoration to the original voice by adjusting the pitch. Therefore, since broadcast voice modulation methods cannot properly protect the identity of the speaker and are vulnerable to security, a new voice modulation method is needed to replace them. In this paper, using the Lightweight speech de-identification model as the evaluation target model, we compare speech de-identification performance with broadcast voice modulation method using pitch modulation. Among the six modulation methods in the Lightweight speech de-identification model, we experimented on the de-identification performance of Korean speech as a human test and EER(Equal Error Rate) test compared with broadcast voice modulation using three modulation methods: McAdams, Resampling, and Vocal Tract Length Normalization(VTLN). Experimental results show VTLN modulation methods performed higher de-identification performance in both human tests and EER tests. As a result, the modulation methods of the Lightweight model for Korean speech has sufficient de-identification performance and will be able to replace the security-weak broadcast voice modulation.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11a
• /
• pp.739-741
• /
• 2005

컴퓨터 게임 지리정보시스템(GIS), 가상현실 분야 등에서 환경 표현의 기반이 되는 지형 렌더링 기술은 매우 중요하다. 최근 LIDAR와 같은 3D 스캐닝 기술은 보다 정밀하고 정확한 지형 데이터를 제공한다. 하지만, 실시간 렌더링을 위해 사용되는 대부분의 방법들이 DEM이나 DTED와 같은 정규격자(uniform grid) 데이터에 최적화 되어 있기 때문에, LIDAR 데이터와 같은 비정규 데이터에는 적합하지 않다. 또한 방대한 LIDAR 데이터는 일반 PC에서 처리가 쉽지 않다. 본 논문에서는 대용량 비정규 데이터에서의 빠르고 효율적인 렌더링 방법을 제안한다. 샘플 데이터의 공간적 분포에 따라 정규격자를 생성하고, 이 격자에 맞도록 LIDAR 데이터를 재샘플링(resampling)하여 DTED와 같은 형태로 변환한다. 기하 재구성된 데이터에 연속적인 상세단계(CLOD)기반의 쿼드트리 알고리듬을 적용하여 지형을 효율적으로 렌더링한다.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.38 no.2
• /
• pp.65-73
• /
• 2013

In the simulation output analysis, bootstrap method is an applicable resampling technique to insufficient data which are not significant statistically. The moving block bootstrap, the stationary bootstrap, and the threshold bootstrap are typical bootstrap methods to be used for autocorrelated time series data. They are nonparametric methods for stationary time series data, which correctly describe the original data. In the simulation output analysis, however, we may not use them because of the non-stationarity in the data set caused by the trend such as increasing or decreasing. In these cases, we can get rid of the trend by differencing the data, which guarantees the stationarity. We can get the bootstrapped data from the differenced stationary data. Taking a reverse transform to the bootstrapped data, finally, we get the pseudo-samples for the original data. In this paper, we introduce the applicability of bootstrap methods to the time series data having trend, and then verify it through the statistical analyses.

• Korean Journal of Organic Agriculture
• /
• v.21 no.4
• /
• pp.487-500
• /
• 2013

The purpose of this study is to estimate efficiency of environmental-friendly agricultural product by using Data Envelopment Analysis. A proposed method employs a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. The technical efficiency, pure technical efficiency, and scale efficiency measure of strawberry by pesticide-free certification is 0.967, 0.995, 0.968 respectively. However those of bias-corrected estimates are 0.918, 0.983, 0.934. We know that the DEA estimator is an upward biased estimator. In technical efficiency, average lower and upper confidence bounds of 0.807 and 0.960. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.

• Proceedings of the Acoustical Society of Korea Conference
• /
• spring
• /
• pp.39-42
• /
• 2000

A bootstrap and aggregating (bagging) vector quantization (VQ) classifier is proposed for speaker recognition. This method obtains multiple training data sets by resampling the original training data set, and then integrates the corresponding multiple classifiers into a single classifier. Experiments involving a closed set, text-independent and speaker identification system are carried out using the TIMIT database. The proposed bagging VQ classifier shows considerably improved performance over the conventional VQ classifier.

• Journal of Korean Society for Quality Management
• /
• v.26 no.4
• /
• pp.250-264
• /
• 1998

The purpose of the thesis is to develop simulation program for forecasting of optical connector. So we can achieve the time and the money saving for making the optical connector. Optical performance (insertion loss) of optical connector mainly relies on 3 misalignment factors-ferrule factor due to mis-manufacture from design, auto-centering effect that is fiber behavior phenomena between hole and fiber, fiber misalignment factor. Simulation use experimental data with auto-centering effect and fiber factor and use pseudo data with ferrule through random number generation because it is developing stage. In this study we a, pp.y kernel density estimation method with experimental data in order to know whether it belong to or not specific parametric distribution family. And we simulate to forecast insertion loss of optical multifiber connector under specific design model using nonparametric bootstrap resampling data and parametric pseudo samples from uniform distribution. We obtain the tolerance specifications of misalignment factors satisfying not exceed in maximum 1.0dB and choose optimal hole diameter.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.1
• /
• pp.1-6
• /
• 2010

The Analytic Hierarchy Process (AHP) has been applied widely in various decision making fields. One of advantages of the AHP is the consistency test. However, it has several problems such as the limit of its concept, the limit of 9 scales and stern criteria, contradictory pairwise comparison. In this paper, we propose new criteria for the consistency with more realistic and ideal conditions. To derive the criteria, we conduct the simulation and use the bootstrap method, which is one of resampling techniques in the simulation area.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.211-214
• /
• 2007

With the recent development of spatial information technology, the relative importance of satellite image contents has increased to about 62%, the techniques related to satellite images have improved, and their demand is gradually increasing. Accordingly, a standard processing method for the whole process of collection from satellites to distribution of satellite images is required in many countries for efficient distribution of images and improvement of their utilization. This study presents the processor standardization technique for the preprocessing of satellite images including geometric correction, orthorectification, color adjustment, interpolation for DEM (Digital Elevation Model) production, rearrangement, and image data management, which will standardize the subjective, complex process and improve their utilization by making it easy for general users to use them

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2010.07a
• /
• pp.161-163
• /
• 2010

한국의 DMB 서비스는 이미 대중화되어 많은 이용자들이 편리하게 이용하고 있으나, 송출되는 DMB 컨텐츠의 해상도에 비해 현재 대부분의 디스플레이 장치들은 더 높은 해상도를 지원하고 있으며 따라서 다양한 방법의 영상 재표본화 기술을 채용하고 있다. 특히 휴대용 장비의 경우 연산량 문제로 저품질의 영상을 제공하게 되고 따라서 이용자들의 만족도가 떨어지게 되었다. 일반적으로 주관적인 영상의 품질은 영상 내 개체에 대한 인식률에 따라 결정되며 에지에서의 개체 간 구분이 명확할수록 증가한다. 본 연구에서는 H.264 동영상 부호화 방법에서 사용되는 인트라 예측 정보와 Total Coefficient 정보를 이용하여 에지 정보를 추출하고 이에 따라 선택적으로 보간법을 적용하여 최대한 연산량을 줄이면서 선명함을 유지할 수 있는 방법을 제안한다.

• Korean Journal of Organic Agriculture
• /
• v.26 no.1
• /
• pp.33-41
• /
• 2018

The paper aims to estimate efficiency of watermelon by using a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. We use the input-output data for watermelon 107 farmers. The main results are as follows. The estimates of efficiency depends on the methodology. The estimates of general DEA is greater than the bootstrapping method. The technical efficiency and pure technical efficiency measure of watermelon is 0.72, 0.82 respectively. However the bias-corrected estimates are less than those of DEA. We know that the DEA estimator is an upward biased estimator. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.