• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.87-92
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• 2023

With the continuous development of the speech recognition system, the recognition rate for speech has developed rapidly, but it has a disadvantage in that it cannot accurately recognize the voice due to the noise generated by mixing various voices with the noise in the use environment. In order to increase the vocabulary recognition rate when processing speech with environmental noise, noise must be removed. Even in the existing HMM, CHMM, GMM, and DNN applied with AI models, unexpected noise occurs or quantization noise is basically added to the digital signal. When this happens, the source signal is altered or corrupted, which lowers the recognition rate. To solve this problem, each voice In order to efficiently extract the features of the speech signal for the frame, the MFCC was improved and processed. To remove the noise from the speech signal, the noise removal method using the Gaussian model applied noise deviation estimation was improved and applied. The performance evaluation of the proposed model was processed using a cross-correlation coefficient to evaluate the accuracy of speech. As a result of evaluating the recognition rate of the proposed method, it was confirmed that the difference in the average value of the correlation coefficient was improved by 0.53 dB.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.107-113
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• 1997

In this paper, an interfacing method to control rehabilitation assitance system with bio-signal is proposed. Controlling with EMG signals method has certain advantage on signal-collecting, but has some drawbacks in the function resolution of EMG signals because data-processing process is not efficient. To improve function-resolution and to increase the efficiency of EMG signal interfacing with rehabilitation assistance system, Multi-layer Perception which is highly effective with static signal and hidden-Markov model for dynamic signal resolving are fused together. In proposed method. The direction and average speed of the rehabilitation assitance system are controlled by the trajectory control and estimation of the moving direction result from the fused model. From the experiment, proposed GMM and 2-level MLP hybrid-classifier yielded 8.6% perception-error rate, improving function resolution. New acceleration control method constructed with 3 nested linear filter produced continuous acceleration paths without the information of destination point. Thus, the mass output caused by non- continuous acceleration-deceleration was eliminated. In the simulation, the necessary calculation, in the case of multiplication, was reduced by 11.54%.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.88-93
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• 2020

Based on the capture-emission energy (CEE) maps of CMOS devices, a physics-informed machine learning model for the bias temperature instability (BTI)-induced threshold voltage shifts and low frequency noise is presented. In order to incorporate physics theories into the machine learning model, the integration of artificial neural network (IANN) is employed for the computation of the threshold voltage shifts and low frequency noise. The model combines the computational efficiency of IANN with the optimal estimation of Gaussian mixture model (GMM) with soft clustering. It enables full lifetime prediction of BTI under various stress and recovery conditions and provides accurate prediction of the dynamic behavior of the original measured data.

• Management & Information Systems Review
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• v.33 no.3
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• pp.21-33
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• 2014

This study investigated the effect of protection of property right on foreign direct investment. With the US. multinational corporations over the periods from 2000 to 2008, this study used the FEM and system GMM, and found that the change of protection of property right level positively affects attracting foreign direct investment while protection of property right level itself does not. In the analyses on high income and low income countries(by income level), only the change of protection of property right level positively affects attracting foreign direct investment in low income countries. In considering the problem of heteroscedasticity on the error term, this study used FGLS and PCSE estimation methods. It is reported that the change of protection of property right level positively affects attracting foreign direct investment while protection of property right level itself does not. And only the change of protection of property right level positively affects attracting foreign direct investment in low income countries. This result means the change of protection of property right level is a key determinant to attract foreign direct investment.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.265-273
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• 2018

In this paper, we propose an acoustic event detection method in tunnels using non-negative tensor factorization (NTF) and hidden Markov model (HMM) applied to multi-channel audio signals. Incidents in tunnel are inherent to the system and occur unavoidably with known probability. Incidents can easily happen minor accidents and extend right through to major disaster. Most incident detection systems deploy visual incident detection (VID) systems that often cause false alarms due to various constraints such as night obstacles and a limit of viewing angle. To this end, the proposed method first tries to separate and detect every acoustic event, which is assumed to be an in-tunnel incident, from noisy acoustic signals by using an NTF technique. Then, maximum likelihood estimation using Gaussian mixture model (GMM)-HMMs is carried out to verify whether or not each detected event is an actual incident. Performance evaluation shows that the proposed method operates in real time and achieves high detection accuracy under simulated tunnel conditions.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.5
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

• Journal of Korea Trade
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• v.25 no.4
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• pp.146-163
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• 2021

Purpose - This paper examines China's impact on Korea's ICT exports considering the direct competition channel, the production shift channel, and the indirect demand channel at once. This paper also takes China's economic rebalancing into account and discusses whether it makes any differences in the effect of the three channels. Design/methodology - To quantify the effect of the three channels, I constructed a linear panel regression model and estimated it with various estimation methods including the system GMM. China's exports toward the same destination as Korea's exports, Korea's exports toward China, and the third countries' exports toward China respectively reflect the three channels. China's GVC indicators are included as well to evaluate the effect of further China's economic rebalancing. Since the present paper has a greater interest in the effect of China rather than the determinant of bilateral trade, a (fixed effect) panel model becomes more appropriate than the gravity model because timeinvariant variables in the gravity model, such as the distance and the language, are eliminated during the estimation process. Findings - The estimation results indicate that Chinese ICT exports are complementary to Korea's ICT exports in general. However, when markets are considered in subgroups, China's ICT exports could have a negative effect in the long run, especially for SITC75 and SITC76 markets, implying a possible competitive threat of China. The production shift effect turns significant during China's economic rebalancing in the markets for the advanced economies and the SITC76 product. China's indirect demand channel is also in effect significantly for the advanced economy and SITC75 commodities during China's economic rebalancing periods. In addition, this paper shows that China's transition toward upstream in the global value chain could have a positive impact on Korea's ICT exports, especially at the Asian market. Originality/value - The contribution of this paper is threefold. First, it focuses on the ICT industry for which Korea increasingly depends on China and China becomes a global hub of the GVC. Second, this paper quantitatively studies three channels in a model in contrast to the literature which mostly examines those channels separately and pays less attention to the GVC aspect. Third, by utilizing relatively recent data from the period of 2001-2017, this paper discusses whether China's economic rebalancing affects the three channels.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.707-715
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• 2020

Globalization has led to an increase in foreign banks' penetration. It is argued that the presence of foreign banks may affect the banking sector of the host countries in several ways including their competition level. It is mentioned that the presence of the foreign banks could heightened the level of competition in the banking sector. Nonetheless, the impact of the foreign banks on competition could be influenced by the degree of information sharing in the banking industry. This study investigates the role of information sharing in moderating the impact of foreign bank penetration on host banking sector competition in selected developing countries. We employ panel data samples of 54 developing countries during the period from 1998 to 2016. The estimation is carried out using the two-step system of the Generalized Method of Moments (GMM) regression technique. This technique is adopted due to its robustness to all forms of endogeneity. The findings of this study show that the presence of information sharing could affect the relationship between foreign banks' penetration and competition. They suggest that improvement in information sharing by a host country may help foreign banks to improve monitoring and reduce the moral hazard and adverse selection problem.

• Management & Information Systems Review
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• v.37 no.1
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• pp.123-138
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• 2018

In this paper, we use panel dataset from Korean linked worker-firm to analyse the effects of the workforce age structure on the productivity or labor costs. We measure 'labor productivity' as added value per capita, 'cost of labor' as labor cost per capita and estimate a dynamic panel model to study the effects of the workforce age structure on the productivity or labor costs. Empirical analysis results show that the workforce age structure is positively related to productivity and labor costs, but only up to the aged of 35-39. That is, we find that an increase in the proportion of younger workers or elder workers rather than the aged 35-39 has a negative effect on productivity and labor cost. In particular, the difference between the estimation coefficient of productivity and labor cost when the share of workers aged 50 or older is increased instead of the aged 35-39 is higher than the difference between the estimation coefficient of productivity and labor cost when the share of workers aged 30 or younger is increased instead of the aged 35-39. Our results exhibit that it is reasonable for firms to worry about declining productivity of elderly workers, whereas firms already used older workers efficiently, such as by adjusting their labor costs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.679-686
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• 2020

In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.