• Title/Summary/Keyword: Correlated error

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Correlation analysis of linguistic factors in non-native Korean speech and proficiency evaluation (비원어민 한국어 말하기 숙련도 평가와 평가항목의 상관관계)

  • Yang, Seung Hee;Chung, Minhwa
    • Phonetics and Speech Sciences
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    • v.9 no.3
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    • pp.49-56
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    • 2017
  • Much research attention has been directed to identify how native speakers perceive non-native speakers' oral proficiency. To investigate the generalizability of previous findings, this study examined segmental, phonological, accentual, and temporal correlates of native speakers' evaluation of L2 Korean proficiency produced by learners with various levels and nationalities. Our experiment results show that proficiency ratings by native speakers significantly correlate not only with rate of speech, but also with the segmental accuracies. The influence of segmental errors has the highest correlation with the proficiency of L2 Korean speech. We further verified this finding within substitution, deletion, insertion error rates. Although phonological accuracy was expected to be highly correlated with the proficiency score, it was the least influential measure. Another new finding in this study is that the role of pitch and accent has been underemphasized so far in the non-native Korean speech perception studies. This work will serve as the groundwork for the development of automatic assessment module in Korean CAPT system.

Neural Network Time Series Modeling of Sensor Information of Plasma Deposition Equipment (플라즈마 증착 장비 센서 정보의 신경망 시계열 모델링)

  • Kim, You-Seok;Kim, Byung-Whan;Kwon, Gi-Chung;Han, Jeong-Hoon;Shon, Jong-Won
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.102-104
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    • 2006
  • Auto-Correlated time series (ATS) model was constructed by using the backpropagation neural network. The performance of ATS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 4%. By integrating ATS model into equipment software, process quality can be more stringently monitored while improving device throughput.

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Properties of the Frost Layer Formed on a Cold Flat Surface (냉각평판에 형성된 서리층의 물성치)

  • Kim, Sung-Gone;Yang, Dong-Keun;Lee, Kwan-Soo
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.27 no.3
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    • pp.374-380
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    • 2003
  • This paper proposes dimensionless correlations predicting properties of the frost layer formed on a cold flat surface. Experiments are carried out to obtain the correlations with various environmental parameters such as air temperature, air velocity, absolute humidity, and cooling plate temperature. As a result, the frost properties (frost layer thickness, density, surface temperature, thermal conductivity) are correlated as a function of Reynolds number, Fourier number, absolute humidity and non-dimensional temperature by using a dimensional analysis. The correlations agree well with the previous and our experimental data within a maximum error of 10%, and are used to predict the frost properties in the following ranges: Reynolds number of 20216 to 53763, Fourier number of 0.1962 to 2.5128, absolute humidity of 3.22 to 8.47, and non-dimensional temperature of 0.125 to 0.5.

Comparison of Active Contour and Active Shape Approaches for Corpus Callosum Segmentation

  • Adiya, Enkhbolor;Izmantoko, Yonny S.;Choi, Heung-Kook
    • Journal of Korea Multimedia Society
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    • v.16 no.9
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    • pp.1018-1030
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    • 2013
  • The corpus callosum is the largest connective structure in the brain, and its shape and size are correlated to sex, age, brain growth and degeneration, handedness, musical ability, and neurological diseases. Manually segmenting the corpus callosum from brain magnetic resonance (MR) image is time consuming, error prone, and operator dependent. In this paper, two semi-automatic segmentation methods are present: the active contour model-based approach and the active shape model-based approach. We tested these methods on an MR image of the human brain and found that the active contour approach had better segmentation accuracy but was slower than the active shape approach.

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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EXPERIMENTAL IDENTIFICATION ON A GEAR WHINE NOISE IN THE AXLE SYSTEM OF A PASSENGER VAN

  • Kim, S.J.;Lee, S.K.
    • International Journal of Automotive Technology
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    • v.8 no.1
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    • pp.75-82
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    • 2007
  • This paper presents practical work on the reduction of gear whine noise. In order to identify the source of the gear whine noise, transfer paths are searched and analyzed by operational deflection shape analysis and experimental modal analysis. It was found that gear whine noise has an air-borne noise path instead of structure-borne noise path. The main sources of air-borne noise were the two global modes caused by the resonance of an axle system. These modes created a vibro-acoustic noise problem. Vibro-acoustic noise can be reduced by controlling the vibration of the noise source. The vibration of noise source is controlled by the modification of structure to avoid the resonance or to reduce the excitation force. In the study, the excitation force of the axle system is attenuated by changing the tooth profile of the hypoid gear. The modification of the tooth profile yields a reduction of transmission error, which is correlated to the gear whine noise. Finally, whine noise is reduced by 10 dBA.

Nurse-perceived Patient Adverse Events and Nursing Practice Environment

  • Kang, Jeong-Hee;Kim, Chul-Woung;Lee, Sang-Yi
    • Journal of Preventive Medicine and Public Health
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    • v.47 no.5
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    • pp.273-280
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    • 2014
  • Objectives: To evaluate the occurrence of patient adverse events in Korean hospitals as perceived by nurses and examine the correlation between patient adverse events with the nurse practice environment at nurse and hospital level. Methods: In total, 3096 nurses working in 60 general inpatient hospital units were included. A two-level logistic regression analysis was performed. Results: At the hospital level, patient adverse events included patient falls (60.5%), nosocomial infections (51.7%), pressure sores (42.6%) and medication errors (33.3%). Among the hospital-level explanatory variables associated with the nursing practice environment, 'physician-nurse relationship' correlated with medication errors while 'education for improving quality of care' affected patient falls. Conclusions: The doctor-nurse relationship and access to education that can improve the quality of care at the hospital level may help decrease the occurrence of patient adverse events.

Robust Self-Tuning Regulator without Persistent Excitation (지속여기 조건이 없는 강인한 자조 안정기)

  • 김영철;이철희;양흥석
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.11
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    • pp.1207-1218
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    • 1990
  • The lack of persistent excitation (PE) can be the reason of freezing in the recursive least square estimators and the covariance windup in the exponential weighted least square estimators. We present a theoretical analysis of these phenomena and a simple method to check the exciting condition in real time. Using these results and under some conditions such as slowly time varying Plant and a tracking problem for set point, a robust self-tuning regulators without PE is proposed. In this algorithm, when PE is not satisfied, only plant gain is estimated, and then the system parameters are corrected by it. It is shown that the gain adaptive scheme makes the robustness to be improved against modeling error, off-set, and correlated noise etc, by the results of analysis and simulations.

A change point estimator in monitoring the parameters of a multivariate IMA(1, 1) model

  • Sohn, Sun-Yoel;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.525-533
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    • 2015
  • Modern production process is a very complex structure combined observations which are correlated with several factors. When the error signal occurs in the process, it is very difficult to know the root causes of an out-of-control signal because of insufficient information. However, if we know the time of the change, the system can be controlled more easily. To know it, we derive a maximum likelihood estimator (MLE) of the change point in a process when observations are from a multivariate IMA(1,1) process by monitoring residual vectors of the model. In this paper, numerical results show that the MLE of change point is effective in detecting changes in a process.

Transform domain algorithm for Improving Convergence Speed of Broadband Active Noise Control (광대역 능동소음제어의 수렴속도개선을 위한 변환영역 알고리듬)

  • Ahn, Doo-Soo;Kim, Jong-Boo;Lee, Tae-Pyo;Yim, Kook-Hyun
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.644-646
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    • 1998
  • The main drawback of filtered-X LMS(FXLMS) algorithm for the ANC of broadband noises is its low convergence speed when the filtered reference signals are strongly correlated, producing a large eigenvalue spread in correlation matrix. This correlation can be caused either by autocorrelation of the signals of the reference sensors, or by coupling between the error path which introduces intercorrelation in the filtered reference signals. In this paper, we introduce a transform domain FXLMS(TD-FXLMS) algorithm that has a high convergence speed by orthogonal transform's decorrelation properties.

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