• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.371-384
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• 2011

Three experiments were carried out to examine how LED lighting hues influence to the rating and recognition of affective stimuli. In Experiment 1 and 2, IAPS affective pictures were used and an affective rating(valence and arousal) task and a recognition memory task were conducted under red, green, blue, and white hue LED lightings in Experiment 1 and cyan, magenta, yellow, and white ones in Experiment 2, respectively. In Experiment 3, affective words were used and the same two tasks were conducted under red, green, blue, and white hue LED lightings. According to the results of affective rating tasks, when primary hues(RGB) were used, red LED lighting elicited an excitement at the arousal dimension and green LED lighting evoked pleasantness at the valence one. When secondary hues(CMY) were used, magenta and cyan showed the similar but weaker patterns of responses comparing to red and green. The results of recognition memory task showed that the responses to the picture stimuli presented at green and cyan hue lightings tended to be a bit faster comparing to the stimuli presented at the other conditions but the difference was insignificant. In Experiment 3, however, recognition memory responses to the affective words presented at green hue lighting were faster significantly. These results indicate that warm colors like red and magenta elicit unpleasantness or excitement while cool colors like green and cyan evoke pleasantness or relaxation, and the primary hues provoke more positive or negative affectivity than secondary ones do. Particularly, the result of recognition memory task in Experiment 3 suggests that green hue LED lighting might be advantageous at the memory performance of language stimuli rather than visual ones.

• Speech Sciences
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• v.11 no.1
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• pp.7-20
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• 2004

In this paper, we propose a two-step noise compensation algorithm in feature extraction for achieving robust speech recognition. The proposed method frees us from requiring a priori information on noisy environments and is simple to implement. First, in frequency domain, the Harmonics-based Spectral Subtraction (HSS) is applied so that it reduces the additive background noise and makes the shape of harmonics in speech spectrum more pronounced. We then apply a judiciously weighted variance Feature Vector Normalization (FVN) to compensate for both the channel distortion and additive noise. The weighted variance FVN compensates for the variance mismatch in both the speech and the non-speech regions respectively. Representative performance evaluation using Aurora 2 database shows that the proposed method yields 27.18% relative improvement in accuracy under a multi-noise training task and 57.94% relative improvement under a clean training task.

• Speech Sciences
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• v.10 no.1
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• pp.71-84
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• 2003

In the acoustic modeling for large vocabulary speech recognition, a sparse data problem caused by a huge number of context-dependent (CD) models usually leads the estimated models to being unreliable. In this paper, we develop a new clustering method based on the C45 decision-tree learning algorithm that effectively encapsulates the CD modeling. The proposed scheme essentially constructs a supervised decision rule and applies over the pre-clustered triphones using the C45 algorithm, which is known to effectively search through the attributes of the training instances and extract the attribute that best separates the given examples. In particular, the data driven method is used as a clustering algorithm while its result is used as the learning target of the C45 algorithm. This scheme has been shown to be effective particularly over the database of low unknown-context ratio in terms of recognition performance. For speaker-independent, task-independent continuous speech recognition task, the proposed method reduced the percent accuracy WER by 3.93% compared to the existing rule-based methods.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.195-198
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• 2002

One-dimensional radar signature, such as range profile, is highly dependent on the aspect angle. Therefore, radar target recognition over wide angular region is a very difficult task. In this paper, we propose the Bayes classifier with Gaussian mixture model for radar target recognition over wide-angular region and compare performances of proposed technique and radar target recognition with subclasses concept in the literature of probability of correct classification ratio.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1052-1057
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• 1994

Dynamically localized self-organizing map model (DLSMM) is a new speech recognition model based on the well-known self-organizing map algorithm and dynamic programming technique. The DLSMM can efficiently normalize the temporal and spatial characteristics of speech signal at the same time. Especially, the proposed can use contextual information of speech. As experimental results on ten Korean digits recognition task, the DLSMM with contextual information has shown higher recognition rate than predictive neural network models.

• Korean Journal of Biological Psychiatry
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• v.11 no.2
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• pp.155-164
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• 2004

Objective:The present study examined the association between basic neurocognitive functions and emotional recognition in chronic schizophrenia. Furthermore, to Investigate cognitive variable related to emotion recognition in Schizophrenia. Methods:Forty eight patients from the Yongin Psychiatric Rehabilitation Center were evaluated for neurocognitive function, and Emotional Recognition Test which has four subscales finding emotional clue, discriminating emotions, understanding emotional context and emotional capacity. Measures of neurocognitive functioning were selected based on hypothesized relationships to perception of emotion. These measures included:1) Letter Number Sequencing Test, a measure of working memory;2) Word Fluency and Block Design, a measure of executive function;3) Hopkins Verbal Learning Test-Korean version, a measure of verbal memory;4) Digit Span, a measure of immediate memory;5) Span of Apprehension Task, a measure of early visual processing, visual scanning;6) Continuous Performance Test, a measure of sustained attention functioning. Correlation analyses between specific neurocognitive measures and emotional recognition test were made. To examine the degree to which neurocognitive performance predicting emotional recognition, hierarchical regression analyses were also made. Results:Working memory, and verbal memory were closely related with emotional discrimination. Working memory, Span of Apprehension and Digit Span were closely related with contextual recognition. Among cognitive measures, Span of Apprehension, Working memory, Digit Span were most important variables in predicting emotional capacity. Conclusion:These results are relevant considering that emotional information processing depends, in part, on the abilities to scan the context and to use immediate working memory. These results indicated that mul- tifaceted cognitive training program added with Emotional Recognition Task(Cognitive Behavioral Rehabilitation Therapy added with Emotional Management Program) are promising.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.2
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• pp.69-77
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• 1993

Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.

• Journal of the Korean Home Economics Association
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• v.40 no.11
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• pp.119-130
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• 2002

This study investigated preschool children's script knowledge according to task situation and socioeconomic status. Subjects were seventy-eight 5-year-old children (38 low- and 40 middle-income children; 36 boys and 42 girls) recruited from three day-care centers in Seoul. Each child participated in the script knowledge assessment session. Assessment of script knowledge consisted of a picture-recognition and picture-sequencing task. Statistical methods used for data analysis were means, standard deviations, repeated measures ANOVA. Results showed that children's script knowledge scores were higher in familiar task situation than in unfamiliar task situation. Furthermore, middle-income children had higher scores of script knowledge than low-income children. Findings of this study indicate that there is the difference of script knowledge between low- and middle-income preschoolers.

• Anxiety and mood
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• v.10 no.1
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• pp.37-43
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• 2014

Objective : Social Phobia is associated with extensive disability and reduced quality of life. The concept of 'social self' is a representation of the self-reflected in the eyes of others, and is recruited during self-face recognition, which is closely related to self-esteem. The aim of this study was to identify the relationship of face recognition for self and others using measures of social anxiety and self-esteem in patients with social phobia. Methods : Twenty-seven patients with social phobia and twenty-three normal controls were evaluated with scales of self-esteem, depression, anxiety and other psychiatric symptoms. All participants completed the self-face recognition task. Nine self-faces, nine other faces and eighty-one morphed faces were presented randomly for each trial. The participants were instructed to make a decision as to whether the stimuli were self-face or not. The responses and reaction times were recorded during the task. Results : There were no group differences of the morphing composition at the recognition start point as self-face. In patients with social phobia, the mean reaction time at the start point of recognizing as a self-face was 1,037.6 ms, which was significantly longer than that of normal controls (911.3 ms, p<0.05). Patients with social phobia showed a significant negative correlation between the mean reaction time and the severity of depression when the stimuli were recognized as a self-face (r=-0.421, p<0.05). Conclusion : A difficulty in attention rather than avoidance may be an important factor of face recognition in patients with social phobia. When considering self-face recognition in such patients, many factors, such as anxiety, depression, working memory and theory of mind, need to be considered.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1680-1684
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• 2009

The priming task was used in order to provide an experimental evidence on whether the processing unit of Korean syllable is antibody or not. Four types of experimental conditions were made: antibody overlap condition (e.g., sumjil -> sungjik), rime overlap condition (e.g.,: hungchik -> sungjik), onset and coda overlap condition (e.g.,: saengjeok -> sungjik), and no overlap condition (e.g.,: chanmeol -> sungjik). In addition, we manipulated the letter type by type and type in order to investigate on whether different degrees of priming are there for the priming task. The result showed that only type showed significant inhibitory effects. This implicates that certain Korean word would be represented and processed by the antibody unit, and further studies are needed to know the whole pattern of Korean word recognition.