• The KIPS Transactions:PartC
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• v.16C no.1
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• pp.27-36
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• 2009

The leaking of personal information is mostly occurred by internal users. The confidential information such as credit card number can be disclosed or modified by system manager easily. The secure storaging and managing scheme for sensitive data of individual and enterprise is required for distributed data management. The manager owning private data is needed to have a weight which is a right to disclose a private data. For deciding a weight, it is required that system is able to designate the level of user's right. In this paper, we propose the new algorithm named digit-independent algorithm. And we propose a new data management scheme of gathering and processing the data based on digit-independent algorithm. Our sharing and recovering scheme have the efficient computation operation for managing a large quantity of data using weight table. The proposed scheme is able to use for secure e-business data management and storage in ubiquitous computing environment.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1027-1032
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• 1994

This paper introduces a interword modeling and a Viterbi search method for continuous speech recognition. We also describe a development of a real-time voice dialing system which can recognize around one hundred words and continuous digits in speaker independent mode. For continuous digit recognition, between-word units have been proposed to provide a more precise representation of word junctures. The best path in HMM is found by the Viterbi search algorithm, from which digit sequences are recognized. The simulation results show that a interword modeling using the context-dependent between-word units provide better recognition rates than a pause modeling using the context-independent pause unit. The voice dialing system is implemented on a DSP board with a telephone interface plugged in an IBM PC AT/486.

• Speech Sciences
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• v.1
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• pp.277-283
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• 1997

In this paper, we present a robust recognition algorithm based on the Wiener filtering method as a research tool to develop the Korean Speech recognition system. We especially used Wiener filtering method in cepstrum-domain, because the method in frequency-domain is computationally expensive and complex. Evaluation of the effectiveness of this method has been conducted in speaker-independent isolated Korean digit recognition tasks using discrete HMM speech recognition systems. In these tasks, we used 12th order weighted cepstral as a feature vector and added computer simulated white gaussian noise of different levels to clean speech signals for recognition experiments under noisy conditions. Experimental results show that the presented algorithm can provide an improvement in recognition of as much as from $5\%\;to\;\20\%$ in comparison to spectral subtraction method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.61-67
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• 2004

We propose a new algorithm to generate additional training patterns using the brain-style information processing algorithm, that is, supervised and unsupervised learning models. This will be useful in the case that we do not have enough number of training patterns because of limitation such as time consuming, economic problem, and so on. We adopt the independent component analysis as an unsupervised model for generating exempalr patterns and multilayer perceptions as supervised models for verifying usefulness of the generated patterns. After statistical analysis of the proposed pattern generation algorithm, we verify successful operations of our algorithm through simulation of handwritten digit recognition with various numbers of training patterns.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.662-665
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• 2002

This paper describes a novel converter to implement high-speed binary-to-residue conversion for moduli 2$^{n}$ - 1, 2$^{n}$ , 2$^{n}$ +2$^{\alpha}$/($\alpha$$\in$｛0,1,…,n-1｝) without using look-up table. In our implementation, the high-speed converter can be achieved, because of the modulo addition time is independent of the word length of operands by using the Signed-Digit (SD) adders inside the modulo adders. For a LSI implementation of residue SD number system with ordinary binary system, the proposed binary-to-residue converter is the efficient circuit.cient circuit.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.251-258
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• 2003

A support vector machine (SVM) is supposed to provide a good generalization performance, but the actual performance of a actually implemented SVM is often far from the theoretically expected level. This is largely because the implementation is based on an approximated algorithm, due to the high complexity of time and space. To improve this limitation, we propose ensemble of SVMs by using Bagging (bootstrap aggregating) and Boosting. By a Bagging stage each individual SVM is trained independently using randomly chosen training samples via a bootstrap technique. By a Boosting stage an individual SVM is trained by choosing training samples according to their probability distribution. The probability distribution is updated by the error of independent classifiers, and the process is iterated. After the training stage, they are aggregated to make a collective decision in several ways, such ai majority voting, the LSE(least squares estimation) -based weighting, and double layer hierarchical combining. The simulation results for IRIS data classification, the hand-written digit recognition and Face detection show that the proposed SVM ensembles greatly outperforms a single SVM in terms of classification accuracy.