• 감성과학
• /
• 제14권3호
• /
• pp.371-384
• /
• 2011

LED 조명의 색상이 정서자극의 평정과 재인에 어떤 영향을 미치는지를 알아보기 위하여 세 개의 실험을 실시하였다. 실험 1과 2에서는 IAPS 정서사진을 사용하여 각각 Red, Green, Blue, 및 White와 Cyan, Magenta, Yellow, 및 White의 조명색상조건에서 정서평정(정서가, 각성차원) 과제와 재인기억과제를 실시하였다. 실험 3에서는 정서단어를 사용하여 Red, Green, Blue, 및 White 조명색상조건에서 두 과제를 실시하였다. 실험 결과, 정서평정과제에서는 일차 색상(RGB)의 경우, LED조명 색상이 Red일 때는 흥분을, Green일 때는 유쾌 정서를 유발하였고, 이차 색상(CMY)의 경우, Magenta와 Cyan은 Red와 Green과 유사한 패턴의 정서 반응을 유발하였으나 그 강도는 약하였다. 재인기억과제에서는 실험 1과 실험 2의 경우, Green과 Cyan 조명색상조건에서 제시되었던 사진자극들에 대한 반응이 다른 조명색상조건에서 제시되었던 사진자극들에 비해 약간 빠른 경향이 있었으나 유의미한 차이는 아니었다. 하지만 실험 3에서는 Green 조명색상조건에서 제시되었던 정서단어들에 대한 재인기억반응이 유의미하게 빨랐다. 이러한 결과로 Red나 Magenta와 같은 난색들은 불쾌나 흥분과 관련된 감성을 유발하는 반면, Green이나 Cyan과 같은 한색들은 유쾌나 이완과 같은 감성을 유발하는 경향이 있으며, 일차 색상들이 이차 색상들보다 강한 정적 내지 부적 감성을 유발함을 알 수 있다. 특히 실험 3의 재인 기억과제에서 나타난 결과는 시각 자극보다 언어 자극의 기억수행에 Green 색상의 LED 조명이 더 유리함을 시사한다.

• 음성과학
• /
• 제11권1호
• /
• pp.7-20
• /
• 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.

• 음성과학
• /
• 제10권1호
• /
• pp.71-84
• /
• 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.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2002년도 하계종합학술대회 논문집(1)
• /
• pp.195-198
• /
• 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.

• 한국음향학회:학술대회논문집
• /
• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
• /
• pp.1052-1057
• /
• 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.

• 생물정신의학
• /
• 제11권2호
• /
• pp.155-164
• /
• 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.

• 전자공학회논문지B
• /
• 제30B권2호
• /
• pp.69-77
• /
• 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.

• 대한가정학회지
• /
• 제40권11호
• /
• pp.119-130
• /
• 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.

• 대한불안의학회지
• /
• 제10권1호
• /
• pp.37-43
• /
• 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.

• 한국산학기술학회논문지
• /
• 제10권7호
• /
• pp.1680-1684
• /
• 2009

한글 단어 재인에 있어서 음절 내 단위가 음절체인지에 관한 실험증거를 제공하기 위하여 점화과제를 사용하였다. 실험조건으로 음절체가 중복되는 조건 (예: 섬질 -> 성직), 각운이 중복되는 조건 (예: 헝칙 -> 성직), 초성과 종성이 중복되는 조건 (예: 생적 -> 성직), 그리고 아무런 철자도 중복되지 않는 조건 (예: 찬멸 -> 성직)를 서로 비교하였다. 또한 목표자극의 글자 유형을 <각> 형과 <곡> 형으로 구분하여 차별적인 점화효과가 일어나는지를 알아보았다. 실험 결과, <각> 형의 목표자극에서만 유의미한 억제 점화 효과가 나타났다. 이는 특정 유형의 단어에 한하여 한글의 단어 재인의 단위가 음절체 일 수 있음을 시사하는 결과이며 보다 다양한 글자 유형에 대하여 점화 효과를 알아보는 연구가 필요하다.