• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.503-506
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• 2001

In this paper, we describe the implementation of a microphone input level control algorithm and the speech improvement with this level controller in personal computer environment. The volume of speech obtained through a microphone affects the speech recognition rate directly. Therefore, proper input volume level control is desired fur better recognition. We considered some conditions for the successful volume controller implementation firstly, then checked its usefulness on our speech recognition system with common office environment speech database. Cepstral mean subtraction is also utilized far the channel-effect compensation of the database. Our implemented controller achieved approximately 50% reduction, i.e., improvement in speech recognition error rate.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.56-63
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• 2008

Image calibration at preprocessing step is very important for face recognition rate improvement, and background noise deletion affects accuracy of face recognition specially. In this paper, a method is proposed to remove background area utilizing elliptical model at preprocessing step for face recognition rate improvement. As human face has the shape of ellipse, a face contour can be easily detected by using the elliptical model in face images.

• Journal of IKEEE
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• v.26 no.1
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• pp.133-136
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• 2022

This paper is about motion gesture recognition system, and proposes the following improvement to the flaws of the current system: a motion gesture recognition system and such algorithm that uses the video image of the entire hand and reading its motion gesture to advance the accuracy of recognition. The motion gesture recognition system includes, an image capturing unit that captures and obtains the images of the area applicable for gesture reading, a motion extraction unit that extracts the motion area of the image, and a hand gesture recognition unit that read the motion gestures of the extracted area. The proposed application of the motion gesture algorithm achieves 20% improvement compared to that of the current system.

• Journal of Society of Preventive Korean Medicine
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• v.7 no.2
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• pp.45-64
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• 2003

This study was conducted to examine the recognition level of the people on oriental medical Services and the need for it's improvement. Data were collected from 1174 residents in Daegu metropolitan city and Gyungbuk province. According to the satisfaction level with each items of oriental medical services, the respondents had positive views on efficacy, kindness, and side-effects. They, however, had negative view on the cost of oriental medical services. In regarding to the priority of improvement of oriental medical system, 'expansion of insurance benefit package' ranked first. Followed by 'safety of herbal medicine(heavy metal/pesticides)', 'improvement of scientific methods and diagnostic technique' etc. For the further development of oriental medical services in the consumer - focused and evidenced-based health care environment, much attention to implement relevant health policy reflecting user's need positively should be made.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.267-270
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• 2016

Currently, tire has a variety of information to know the information of the tire are displayed on the tire side. the market are marked with raised letters showing a variety of information relating to the tires. Such information enables people and tire related companies to distinguish between tires upon the information marked on the tires. Generally, people see the information including max press, manufacturing date, etc. Accordingly, studies on automated recognition of raised letters on tire by using image processing technology have been presented consistently. However, they lack a method for recognition of letters and improvement of the recognition. Moreover, the raised letters have been previously recognized through image processing. Further, to obtain the character recognition of a conventional side in video, it is suitably utilized the effects of lighting time of acquisition, so as part of the background and the character has a gray level values between approximately the same, is the part that is not relatively clear are many scattered. In this paper, we see the characters of the tire side using the laser sensor, recognition, was designed for character recognition of the tire side.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.358-363
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• 1994

This paper presents the improvement of the SCHMM using discrete VQ and One-Pass algorithm for keywords recognition in Korean continuous speech. The SCHMM using discrete VQ is a simple model that is composed of a variable mixture gaussian probability density function with dynamic mixture number. One-Pass algorithm is improved such that recognition rates are enhanced by fathoming any undesirable semisyllable with the low likelihood and the high duration penalty, and computation time is reduced by testing only the frame which is dissimilar to the previously testd frame. In recognition experiments for speaker-dependent case, the improved One-Pass algorithm has shown recognition rates as high as 99.7% and has reduced compution time by about 30% compared with the currently abailable one-pass algorithm.

• Phonetics and Speech Sciences
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• v.6 no.2
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• pp.29-34
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• 2014

In the Vector Taylor Series (VTS)-based noisy speech recognition methods, Hidden Markov Models (HMM) are usually trained with clean speech. However, better performance is expected by training the HMM with noisy speech. In a previous study, we could find that Minimum Mean Square Error (MMSE) estimation of the training noisy speech in the log-spectrum domain produce improved recognition results, but since the proposed algorithm was done in the log-spectrum domain, it could not be used for the HMM adaptation. In this paper, we modify the previous algorithm to derive a novel mathematical relation between test and training noisy speech in the cepstrum domain and the mean and covariance of the Multi-condition TRaining (MTR) trained noisy speech HMM are adapted. In the noisy speech recognition experiments on the Aurora 2 database, the proposed method produced 10.6% of relative improvement in Word Error Rates (WERs) over the MTR method while the previous MMSE estimation of the training noisy speech produced 4.3% of relative improvement, which shows the superiority of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.73-80
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• 2010

Vocabulary recognition system is providing inaccurate vocabulary and similar phoneme recognition due to reduce recognition rate. It's require method of similar phoneme recognition unrecognized and efficient feature extraction process. Therefore in this paper propose phoneme likelihood error correction improvement system using based on phoneme feature Bhattacharyya distance measurement. Phoneme likelihood is monophone training data phoneme using HMM feature extraction method, similar phoneme is induced recognition able to accurate phoneme using Bhattacharyya distance measurement. They are effective recognition rate improvement. System performance comparison as a result of recognition improve represent 1.2%, 97.91% by Euclidean distance measurement and dynamic time warping(DTW) system.

• Journal of Environmental Health Sciences
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• v.41 no.6
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• pp.380-388
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• 2015

Objectives: Poisonous substances experts engage in policymaking regarding poisonous substances, whereas poisonous substances managers perform legal duties related to poisonous substances management systems at worksites. To understand and improve poisonous substances designation systems, it is necessary to distinguish the roles of these experts and managers. We further aimed to identify problems with poisonous substances appointment systems and provide basic data for their improvement by investigating the knowledge and recognition of the need for system improvement among managers and experts. Methods: To determine the $subjects^{\circ}{\emptyset}$ awareness of poisonous substances designation systems, a selfadministered questionnaire comprised of items on general characteristics and knowledge and recognition of the need for system improvement was issued. Data were analyzed via t-tests and ANOVA using SPSS v 16.0 Results: Regarding system comprehension, managers (n=213; mean 3.28, SD 0.63) significantly differed from experts (n=35; mean 4.08, SD 0.59) (P<0.001). No differences were found in recognition of need for improvement between managers (mean 3.11, SD 0.34) and experts (mean 3.24, SD 0.31). Significant differences in comprehension were found among managers by education level (P<0.05) and company size (P<0.05). Regarding industry type, comprehension was greater in the electrical/electronic and chemical/environmental industries compared to in other industries (P = 0.066). Comprehension was higher among those with five years or more of experience compared to those with less than five years. Regarding recognition of need for improvement, managers showed significant differences by company size (P<0.05). $Experts^{\circ}{\emptyset}$ comprehension showed no differences by general characteristics, while need for improvement differed according to work experience (P<0.001). Conclusion: The study found that the bigger the company size, the higher the level of comprehension by managers and the experts. In the case of both groups, where a higher comprehension of the poisonous substances designation system was evident, they recognized the necessity of its improvement.

• MALSORI
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• no.44
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• pp.105-113
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• 2002

In Korean, each digit is monosyllable and some pairs are known to have high confusability, causing performance degradation of connected digit recognition systems. To improve the performance, in this paper, we employ various discriminant analyses (DA) including Linear DA (LDA), Weighted Pairwise Scatter LDA WPS-LDA), Heteroscedastic Discriminant Analysis (HDA), and Maximum Likelihood Linear Transformation (MLLT). We also examine several combinations of various DA for additional performance improvement. Experimental results show that applying any DA mentioned above improves the string accuracy, but the amount of improvement of each DA method varies according to the model complexity or number of mixtures per state. Especially, more than 20% of string error reduction is achieved by applying MLLT after WPS-LDA, compared with the baseline system, when class level of DA is defined as a tied state and 1 mixture per state is used.