• The Journal of the Acoustical Society of Korea
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• v.22 no.3E
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• pp.124-132
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• 2003

We propose a new method for speech/non-speech classifiers based on concepts of the adaptive boosting (AdaBoost) algorithm in order to detect speech for robust speech recognition. The method uses a combination of simple base classifiers through the AdaBoost algorithm and a set of optimized speech features combined with spectral subtraction. The key benefits of this method are the simple implementation, low computational complexity and the avoidance of the over-fitting problem. We checked the validity of the method by comparing its performance with the speech/non-speech classifier used in a standard voice activity detector. For speech recognition purpose, additional performance improvements were achieved by the adoption of new features including speech band energies and MFCC-based spectral distortion. For the same false alarm rate, the method reduced 20-50% of miss errors.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.165-170
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• 2013

In this paper, we propose the information acquisition and analysis system for a vehicle driver in order to provide the safe driving environments. We first define the list of reckless driving behaviors and propose the recognition system, which recognizes the reckless behaviors, by using the acquired information. The collaboration among the information acquisition, the analysis, and the behavior comparison modules increases the accuracy of the recognition rate. Our system alarms to a vehicle driver in order to notify the potential to confront the dangerous situation due to the abnormal or reckless driving behaviors.

• ETRI Journal
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• v.35 no.6
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• pp.1048-1057
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• 2013

In recent years, augmented reality (AR) technologies have been the subject of great interest among many communities. In education applications, old-fashioned materials (or textbooks) are still used, despite remarkable AR developments in the industrial area. We present an AR system for education. Our system consists of an authoring tool that can be used to create educational content, a viewer that plays that content, and an engine to manage the tool and viewer. In our system, a marker unit recognizes a marker printed on a plane or a cubic plane by adaptively adjusting the threshold to have an excellent recognition rate in diverse environments and acquires corresponding data of the marker. Based on the system, we test 142 elementary school students for increased educational benefits using our system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.187-196
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• 1996

This paper introduces the concept of fixed weights and proposes an algorithm for classification by adding this concept to vector space separation method in LVQ. The proposed algorithm is based on competitive learning. It uses fixed weightsfor generality and fast adaptation efficient radius for new weight creation, and L1 distance for fast calcualtion. It can be applied to many fields requiring adaptive learning with the support of generality, real-tiem processing and sufficient training effect using smaller data set. Recognition rate of over 98% for the train set and 94% for the test set was obtained by applying the suggested algorithm to on-line handwritten recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1500-1505
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• 1999

In this paper, we presented the stereo algorithm for 3-D object recognition. In order to solve the problem for matching time in existed methods, we proposed the method which used the moving direction vector. On the other hand, after we extracted the moving vectors by moving direction of objects, rotated object was matched on axis of it. Using the Hough transform, we obtained the 2-D synthesed image as reference images corresponding to the rate of moving, and then compared with the unknown input images.

• Speech Sciences
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• v.12 no.2
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• pp.183-191
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• 2005

This paper describes the automated call routing for call center system based on speech recognition. We focus on the task of automatically routing telephone calls based on a users fluently spoken response instead of touch tone menus in an interactive voice response system. Vector based call routing algorithm is investigated and normalization method suggested. Call center database which was collected by KT is used for call routing experiment. Experimental results evaluating call-classification from transcribed speech are reported for that database. In case of small training data, an average call routing error reduction rate of 9% is observed when normalization method is used.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.481-485
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• 1989

The object of this parer is on the design of an broad board classifier for connected. Korean digit. Many approaches have been applied in speech recognition systems: parametric vector quantization, dynamic programming and hiden Markov model. In the 80's the neural network method, which is expected to solve complex speech recognition problems, came bach. We have chosen the rule based system for our model. The phoneme-groups that we wish to classify are vowel_like, plosive_like fricative_like, and stop_like.The data used are 1380 connected digits spoken by three untrained male speakers. We have seen 91.5% classification rate.

• International Journal of Contents
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• v.7 no.3
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• pp.6-12
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• 2011

In this paper, we show how such enhancement of Farwell-Donchin BCI enables a fresh, inexperienced user to achieve quickly an accurate BCI control with a high information transfer rate. This paper presents the results of a BCI experiment where the participant, who had no previous BCI experience, obtained, in about 20 min, a highly reliable and fast control over the BCI spelling device based on the Farwell-Donchin paradigm. Offline analysis showed that the high performance of the BCI was, to a high extent, due to the use of the ERP component N1, in addition to component P300, which has been considered the only ERP component important for the prediction of user's choice in the Farwell-Donchin paradigm in many publications.

• MALSORI
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• no.59
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• pp.13-25
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• 2006

In previous study, the linlog(linear log) RASTA(J-RASTA) approach based on PLP was proposed to deal with both the channel effect and the additive noise. The extraction of PLP required generally more steps and computation than the extraction of widely used MFCC. Thus, in this paper, we apply the linlog function to the MFCC for investigating the possibility of simple compensation method that removes both distortion. With the experimental results, the proposed method shows the similar tendency to the linlog RASTA-PLP_ When the J value is set to le-6, the best ERR(Error Reduction Rate) of 33% is obtained. For applying the linlog function to the feature extraction process, the J value plays a very important role in compensating the corruption. Thus, the study for the adaptive J or noise dependent J estimation is further required.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.129-137
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• 1994

In this paper, a new texture feature extraction method for texture image classification is proposed. The proposed method is a modified texture spectrum method. It uses local weighting averaged texture unit, that is, the neighbor pixels are weithted and averaged in 4-direction and the calculated values are compared with center pixel to find texture units. The proposed method has only 81 texture units and these units are really good features for texture classification. The proposed method is applied to vegetable images and Blodatz album images and compared with several conventional methods for the feature extraction time and the recognition rate.