• Title/Summary/Keyword: normalized score

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Machine scoring method for speech recognizer detection mispronunciation of foreign language (외국어 발화오류 검출 음성인식기를 위한 스코어링 기법)

  • Kang, Hyo-Won;Bae, Min-Young;Lee, Jae-Kang;Kwon, Chul-Hong
    • Proceedings of the KSPS conference
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    • 2004.05a
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    • pp.239-242
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    • 2004
  • An automatic pronunciation correction system provides users with correction guidelines for each pronunciation error. For this purpose, we propose a speech recognition system which automatically classifies pronunciation errors when Koreans speak a foreign language. In this paper, we also propose machine scoring methods for automatic assessment of pronunciation quality by the speech recognizer. Scores obtained from an expert human listener are used as the reference to evaluate the different machine scores and to provide targets when training some of algorithms. We use a log-likelihood score and a normalized log-likelihood score as machine scoring methods. Experimental results show that the normalized log-likelihood score had higher correlation with human scores than that obtained using the log-likelihood score.

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Machine Scoring Methods Highly-correlated with Human Ratings in Speech Recognizer Detecting Mispronunciation of Foreign Language (한국인의 외국어 발화오류검출 음성인식기에서 청취판단과 상관관계가 높은 기계 스코어링 기법)

  • Bae, Min-Young;Kwon, Chul-Hong
    • Speech Sciences
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    • v.11 no.2
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    • pp.217-226
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    • 2004
  • An automatic pronunciation correction system provides users with correction guidelines for each pronunciation error. For this purpose, we develop a speech recognition system which automatically classifies pronunciation errors when Koreans speak a foreign language. In this paper, we propose a machine scoring method for automatic assessment of pronunciation quality by the speech recognizer. Scores obtained from an expert human listener are used as the reference to evaluate the different machine scores and to provide targets when training some of algorithms. We use a log-likelihood score and a normalized log-likelihood score as machine scoring methods. Experimental results show that the normalized log-likelihood score had higher correlation with human scores than that obtained using the log-likelihood score.

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Association of Nose Size and Shapes with Self-rated Health and Mibyeong (코의 크기 및 형태와 자가건강, 미병과의 상관성)

  • Ahn, Ilkoo;Bae, Kwang-Ho;Jin, Hee-Jeong;Lee, Siwoo
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.35 no.6
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    • pp.267-273
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    • 2021
  • Mibyeong (sub-health) is a concept that represents the sub-health in traditional East Asian medicine. Assuming that the nose sizes and shapes are related to respiratory function, in this study, we hypothesized that the nose size and shape features are related to the self-rated health (SRH) level and self-rated Mibyeong severity, and aimed to assess this relationship using a fully automated image analysis system. The nose size features were evaluated from the frontal and profile face images of 810 participants. The nose size features consisted of five length features, one area feature, and one volume feature. The level of SRH and the Mibyeong severity were determined using a questionnaire. The normalized nasal height was negatively associated with the self-rated health score (SRHS) (partial ρ = -0.125, p = 3.53E-04) and the Mibyeong score (MBS) (partial ρ = -.172, p = 9.38E-07), even after adjustment for sex, age, and body mass index. The normalized nasal volume (ρ = -.105, p = 0.003), the normalized nasal tip protrusion length (ρ = -.087, p = 0.014), and the normalized nares width (ρ = -.086, p = .015) showed significant correlation with the SRHS. The normalized nasal area (ρ = -.118, p = 0.001), the normalized nasal volume (ρ = -.107, p = .002) showed significant correlation with the MBS. The wider, longer, and larger the nose, the lower the SRHS and MBS, indicating that health status can be estimated based on the size and shape features of the nose.

The Relationship Between Passive Ankle Dorsiflexion With a Non-Weight Bearing Condition and the Performance of the Dynamic Balance Test (비체중지지자세에서의 수동적 발목 발등굽힘과 동적균형검사 수행력의 상관관계)

  • Park, Jun-Sang;Yang, No-Yul;Kwon, Oh-Yun
    • Physical Therapy Korea
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    • v.22 no.1
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    • pp.30-36
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    • 2015
  • The purpose of this study was to examine the relationships between the ankle dorsiflexion passive range of motion (DF PROM) under a non-weight bearing condition and the normalized reach distance in three directions of the Y-Balance Test (YBT). Sixty-one healthy adults (32 males and 29 females, age: $23.0{\pm}3.0$ years, height: $169.3{\pm}8.9cm$, weight: $61.9{\pm}5.4kg$) participated in this study. The ankle DF PROM was measured using a goniometer. To assess dynamic balance, all subjects performed three trials to determine the maximum lower extremity reach in the anterior, posteromedial, and posterolateral directions of the YBT. The relationship between the ankle DF PROM and both the normalized reach distance in each direction and the composite score of the YBT were analyzed using the Pearson correlation. Only the normalized reach distance in the anterior direction of the YBT was significantly related to the ankle DF PROM measured under a non-weight bearing condition (r=.50, p<.001). Neither the normalized reach distances in the posterior directions nor the composite score of the YBT were significantly correlated with the ankle DF PROM measured under a non-weight bearing condition. These findings suggest that ankle DF PROM does not affect the overall dynamic balance of the lower extremity, with only the anterior dynamic balance affected among the three directions.

Prediction of Power Consumptions Based on Gated Recurrent Unit for Internet of Energy (에너지 인터넷을 위한 GRU기반 전력사용량 예측)

  • Lee, Dong-gu;Sun, Young-Ghyu;Sim, Is-sac;Hwang, Yu-Min;Kim, Sooh-wan;Kim, Jin-Young
    • Journal of IKEEE
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    • v.23 no.1
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    • pp.120-126
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    • 2019
  • Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

SCORE NORMALIZATION FOR A UNIVERSITY GRADES INPUT SYSTEM USING A NEURAL NETWORK

  • Park, Young Ho
    • Korean Journal of Mathematics
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    • v.28 no.4
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    • pp.943-953
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    • 2020
  • A university grades input system requires for professors to enter the normalized total scores for the letter grades and to input the scores from six fields such as Midterm, Final, Quiz which sum up to the total. All six fields have specified bounds which add up to 100. Professors should scale in the total scores to match up the letter grades and scale in every field of each student's original scores within the bounds to sum up to the scaled total score. We solve this problem by a novel design of simple shallow neural network.

A Heuristic Algorithm to Find All Normalized Local Alignments Above Threshold

  • Kim, Sangtae;Sim, Jeong Seop;Park, Heejin;Park, Kunsoo;Park, Hyunseok;Seo, Jeong-Sun
    • Genomics & Informatics
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    • v.1 no.1
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    • pp.25-31
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    • 2003
  • Local alignment is an important task in molecular biology to see if two sequences contain regions that are similar. The most popular approach to local alignment is the use of dynamic programming due to Smith and Waterman, but the alignment reported by the Smith-Waterman algorithm has some undesirable properties. The recent approach to fix these problems is to use the notion of normalized scores for local alignments by Arslan, Egecioglu and Pevzner. In this paper we consider the problem of finding all local alignments whose normalized scores are above a given threshold, and present a fast heuristic algorithm. Our algorithm is 180-330 times faster than Arslan et al.'s for sequences of length about 120 kbp and about 40-50 times faster for sequences of length about 30 kbp.

Comparison of the Functional Ambulation Performance Scores of Senior Adults With or Without a History of Falls (낙상 경험 유무에 따른 노인의 기능적 보행성취도 점수(FAP score) 비교)

  • Kwon, Hyuk-Cheol;Kong, Jin-Yong
    • Physical Therapy Korea
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    • v.10 no.1
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    • pp.1-13
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    • 2003
  • The purpose of the study was to determine if there was a difference in the Functional Ambulation Performance score of senior adults with or without a history of falls during walking at a preferred velocity. Twelve subjects with a history of falling (mean age=73.8) and eight subjects with no history of falling (mean age=70.4) participated in the study. Temporal and spatial parameters of gait were analyzed using the computerized GAITRite system. The GAITRite system integrates specific components of locomotion to provide a single, numerical representation of gait, the Functional Ambulation Performance score. The Functional Ambulation Performance score is a Quantitative means of assessing gait based on specific temporal and spatial parameters. Statistical analysis of the two groups demonstrated a significant decrease in Functional Ambulation Performance score for those with a history of falls. They had lower values for step/extremity ratios, mean normalized velocity, and greater values for step times, percent in double support. These results indicate that the GAITRite system can be useful in detecting footfall patterns and selected time and distance measurements of persons with a history of falls and the Functional Ambulation Performance score can be used as indicators of gait performance for senior adults with a history of falls.

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A method for producing normalized total score of BSC measures (BSC 지표의 정규화된 Total Score 산출 방법)

  • Kim, Su-Yeon;Hwang, Hyun-Seok;Hong, Jong-Yi
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.5
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    • pp.163-172
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    • 2007
  • ESC has been used as a tool for evaluating overall performance of firms. ESC focuses mainly on building a balanced viewpoint comprising perspectives and their metrics. It is, therefore, difficult to value overall strategic achievements of a company derived by consolidating various perspectives and metrics. Because of the absence of a method for consolidating ESC metrics and computing total score based on these metrics, it is difficult to evaluate whole strategic performance and find core obstacle parts of performance. In this paper, we suggest a method of normalizing a numerical value of metrics with different units, and calculating the total score of ESC metrics. We conduct a case study of evaluating the effectiveness of CRM to illustrate the applicability and feasibility of the suggested method.

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Fundamental Research on Spring Season Daytime Sea Fog Detection Using MODIS in the Yellow Sea

  • Jeon, Joo-Young;Kim, Sun-Hwa;Yang, Chan-Su
    • Korean Journal of Remote Sensing
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    • v.32 no.4
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    • pp.339-351
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    • 2016
  • For the safety of sea, it is important to monitor sea fog, one of the dangerous meteorological phenomena which cause marine accidents. To detect and monitor sea fog, Moderate Resolution Imaging Spectroradiometer (MODIS) data which is capable to provide spatial distribution of sea fog has been used. The previous automatic sea fog detection algorithms were focused on detecting sea fog using Terra/MODIS only. The improved algorithm is based on the sea fog detection algorithm by Wu and Li (2014) and it is applicable to both Terra and Aqua MODIS data. We have focused on detecting spring season sea fog events in the Yellow Sea. The algorithm includes application of cloud mask product, the Normalized Difference Snow Index (NDSI), the STandard Deviation test using infrared channel ($STD_{IR}$) with various window size, Temperature Difference Index(TDI) in the algorithm (BTCT - SST) and Normalized Water Vapor Index (NWVI). Through the calculation of the Hanssen-Kuiper Skill Score (KSS) using sea fog manual detection result, we derived more suitable threshold for each index. The adjusted threshold is expected to bring higher accuracy of sea fog detection for spring season daytime sea fog detection using MODIS in the Yellow Sea.