• MALSORI
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• no.54
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• pp.15-26
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• 2005

The aim of this paper was to analyze the lexical effects on spoken word recognition of Korean monosyllabic word. The lexical factors chosen in this paper was frequency, density and lexical familiarity of words. Result of the analysis was as follows; frequency was the significant factor to predict spoken word recognition score of monosyllabic word. The other factors were not significant. This result suggest that word frequency should be considered in speech perception test.

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.77-80
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• 2005

The aim of this paper was to analyze the lexical effects on spoken word recognition of Korean monosyllabic word. The lexical factors chosen in this paper was frequency, density and lexical familiarity of words. Result of the analysis was as follows; frequency was the significant factor to predict spoken word recognition score of monosyllabic word. The other factors were not significant. This result suggest that word frequency should be considered in speech perception test.

• The Journal of the Acoustical Society of Korea
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• v.10 no.3
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• pp.31-36
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• 1991

We propose an efficient pre-classification algorithm extracting candidate words to reduce the recognition time in a large-vocabulary recognition system and also propose the use of spectral and temporal smoothing of the observation probability to improve its classification performance. The proposed algorithm computes the coarse likelihood score for each word in a lexicon using the observation probabilities of speech spectra and duration information of recognition units. With the proposed approach we could reduce the computational amount by 74% with slight degradation of recognition accuracy in 1160-word recognition system based on the phoneme-level HMM. Also, we observed that the proposed coarse likelihood score computation algorithm is a good estimator of the likelihood score computed by the Viterbi algorithm.

• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.385-394
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• 2010

Automatic gain control(AGC) is used in hearing aids to compensate for the hearing level as to reduced dynamic range. AGC is consisted of the main 4 factors which are compression threshold, compression ratio, attack time, and release time. This study especially focus on each individual need for optimum release time parameters that can be changed within 7 certain range such as 12, 64, 128, 512, 2094, and 4096ms. To estimate the effect of various release time in AGC, twelve normal hearing and twelve hearing impaired listeners are participated. The stimuli are used by one syllable and sentence which have the same acoustic energy respectively. Then, each of score of the word recognition score is checked in quiet and noise conditions. As a result, it is verified that most people have the different best recognition score on specific release time. Also, if hearing aids is set by the optimum release time in each person, it is helpful in speech recognition and discrimination.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.464-470
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• 2016

This paper presents a speech recognition database verification system using speech measures, and describes a speech measure extraction algorithm which is applied to this system. In our previous study, to produce an effective speech quality measure for the system, we propose a combination of various speech measures which are highly correlated with WER (Word Error Rate). The new combination of various types of speech quality measures in this study is more effective to predict the speech recognition performance compared to each speech measure alone. In this paper, we increase the system independency by employing GMM acoustic score instead of HMM score which is obtained by a secondary speech recognition system. The combination with GMM score shows a slightly lower correlation with WER compared to the combination with HMM score, however it presents a higher relative improvement in correlation with WER, which is calculated compared to the correlation of each speech measure alone.

• Journal of the Korean Society of School Health
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• v.22 no.1
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• pp.17-32
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• 2009

Purpose: This study was performed to investigate the attitude and recognition on how to describe the elderly of elementary school students. Methods: The subject of this study was total 806 students of 4, 5, 6 grade at 2 elementary schools in Gyunggi-do. The data were collected through self-reporting questionnaires for a month. Results: First, the score of attitude about the elderly was 107.8 and image score was the highest. Second, there were significant differences in the attitude about the elderly according to grade, birth order of siblings, domestic atmosphere, and economic status, domestic education on respect about the elderly, and education about the elderly at school. Third, there were significant differences in the attitude about the elderly according to parent-grandparent relationship, health and economic status of grandparents, meeting frequency with grandparents. Fourth, the score of word recognition about the elderly was 43.3 and social score was the highest. fifth, there were significant differences in recognition on how to describe the elderly according to grade, birth order of siblings of students and parents, domestic atmosphere, and economic status, domestic education on respect about the elderly. Sixth, there were significant differences in recognition on how to describe according to parent-grandparent relationship, health status and economic status of grandparents, meeting frequency with grandparents. Lastly, The attitude and recognition about the elderly showed significant positive relationship. Conclusion: We should provide qualitative education programs to improve the attitude and recognition about the elderly of elementary school students.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.46-50
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• 2001

This paper proposes a new recognition time reduction algorithm Score-Cache technique, which is applicable to the HMM-base speech recognition system. Score-Cache is a very unique technique that has no other performance degradation and still reduces a lot of search time. Other search reduction techniques have trade-offs with the recognition rate. This technique can be applied to the continuous speech recognition system as well as the isolated word speech recognition system. W9 can get high degree of recognition time reduction by only replacing the score calculating function, not changing my architecture of the system. This technique also can be used with other recognition time reduction algorithms which give more time reduction. We could get 54% of time reduction at best.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.321-323
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• 2016

최근 연구에서 기계학습 중 지도학습 방법으로 개체명 인식을 하고 있다. 그러나 지도 학습 방법은 데이터를 만드는 비용과 시간이 많이 필요로 한다. 본 연구에서는 주석 된 말뭉치를 사용하여 지도 학습 방법을 사용 한다. 의생명 개체명 인식은 Protein, RNA, DNA, Cell type, Cell line 등을 포함한 텍스트 처리에 중요한 기초 작업입니다. 그리고 의생명 지식 검색에서 가장 기본과 핵심 작업 중 하나이다. 본 연구에서는 순환형 신경망과 워드 임베딩을 자질로 사용한 조건적 임의 필드에 대한 성능을 비교한다. 조건적 임의 필드에 N_Gram만을 자질로 사용한 것을 기준점으로 설정 하였고, 기준점의 결과는 70.09% F1 Score이다. RNN의 jordan type은 60.75% F1 Score, elman type은 58.80% F1 Score의 성능을 보여준다. 조건적 임의 필드에 CCA, GLOVE, WORD2VEC을 사용 한 결과는 각각 72.73% F1 Score, 72.74% F1 Score, 72.82% F1 Score의 성능을 얻을 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.73-75
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• 2022

Scene Text Recognition is a technology used in the field of artificial intelligence that requires manless robot, automatic vehicles and human-computer interaction. Though scene text images are distorted by noise interference, such as illumination, low resolution and blurring. Unlike previous studies that recognized only English, this paper shows a strong recognition accuracy including various characters, English, Korean, special character and numbers. Instead of selecting only one class having the highest probability value, a candidate word can be generated by considering the probability value of the second rank as well, thus a method can be corrected an existing language misrecognition problem.

• Journal of Biomedical Engineering Research
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• v.30 no.1
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• pp.94-102
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• 2009

In this paper, we propose a hearing impairment simulator considering reduced frequency selectivity of the hearing impaired, and verify it's performance through experiments. The reduced frequency selectivity was embodied by spectral smearing using linear prediction coding(LPC). The experiments are composed of 4 kinds of tests; pure tone test, speech reception threshold(SRT) test, and word recognition score(WRS) test without spectral smearing and with spectral smearing. The experiments of the hearing impairment simulator were performed with 9 subjects who have normal hearing. The amount of spectral smearing was controlled by LPC order. The percentile score of WRS test without smearing is $89.78{\pm}2.420%$. The scores of WRS with 24th LPC order and with 8th LPC order are $88.00{\pm}3.556%$ and $83.78{\pm}2.123%$ respectively. It is verified that WRS score is lowered by decreasing LPC order. This is a reasonable result considering that spectral smearing is getting heavier according to decreasing LPC order. It is confirmed that spectral smearing using LPC simulates the reduced frequency selectivity of the hearing impaired and affects the clearness of speech reception.