한국인 영어 학습자들의 단어 분절 및 인지를 위한 강세 단서 학습

학위논문 (석사)-- 서울대학교 대학원 : 외국어교육과 영어전공, 2016. 8. 안현기.It is known that English native speakers recognize the onset of a word at the stressed syllable (Metrical Segmentation Strategy) but in a large volume of studies, Korean learners of English are not sensitive to stress, and thereby they can't the use stress cue for segmentation effectively. The current study investigated whether Korean learners of English can learn to segment a stream of speech by recognizing the stressed syllable as the onset of a word based on statistical regularity, especially transitional probability (TP). The experiments were conducted for 10 - 13 aged learners of English living in Seoul and divided into two parts: Experiment 1 for learning effects depending on stress patterns and the ways of learning, Experiment 2 for the stress pattern preference of Korean learners of English. In Experiment 1, stimuli were designed with 3 sets of 18 pseudo-words composed of 3 syllables (CVCVCV) and conducted pre- and post- tests. Pre-test was proceeded on TP-only stimuli and the word-spotting test. In the post-test, learning sections were included depending on the stress patterns (word-initial or word-final) and the ways of learning (listening or repeating aloud) and then the participants took the word-spotting test. In Experiment 2, all the participants took the preference test in which they chose what they recognized as a word after listening to 18 chains of a repeated pseudo-word stressed at the initial syllable. As a result of Experiment 1, in the case of being given TP-only cue, Korean learners of English could segment the speech by using TP but this was interfered with when they learned word-initial stressed words by listening. However, when they learned word-initial stressed words by repeating aloud, the accuracy increased and this effect was similar to the case that they learned word-final stressed words by listening. Experiment 2 was investigated whether Korean learners of English showed any preference for stress pattern at word-level. The result showed that approximately 89.7% of the participants tended to recognize a word by word-final stress. Taken together, the current study implies that producing experience can facilitate the accurate perception and segmentation in a new language, which can be explained by Motor Theory. Especially, this result suggests the possibility that segmentation at the word-initially stressed syllable could be learned through producing experience by L2 learners. Furthermore, Korean learners might apply the L1 prosody (L-H tone pattern) to a new language prosodic pattern, which could be interpreted by PAM model or word-final lengthening effects. A number of studies have identified that Korean learners have trouble using the stress cue for segmentation since there is not word level stress in Korean. The results of the current study imply that producing experience is a necessary process not only for speaking but also for perception of the speech. In particular, in order to learn the word level stress cue which does not exist in Korean, the experiences of the direct articulation and the memory of the feature in producing play an important role for the accurate segmentation and perception. This might be a useful way of improving listening skills in the English as a Foreign Language environment such as Korea where listening input is exceedingly limited.Chapter 1. INTRODUCTION 1 1.1 The Purpose of the Studuy 1 1.2 Research Questions 4 1.3 Organization of the Thesis 5 Chapter 2. LITERATURE REVIEW 7 2.1 Word Segmentation Cues in Speech Perception 7 2.2 Statistical Cues for Word Segmentation 10 2.3 Stress Pattern Cues for Word Segmentation 12 2.4 Relation between Perception and Production 16 Chapter 3. METHODOLOGY 22 3.1 Apparatus 22 3.2 Participants 23 3.3 Materials 25 3.4 Experiment 1 27 3.4.1 Phase 1 27 3.4.2 Phase 2 34 3.5 Experiment 2 39 3.6 Data Collection and Analysis 40 Chapter 4. RESULTS AND DISCUSSION 41 4.1 Experiment 1 41 4.1.1 Test Results 41 4.1.2 Discussion 48 4.2 Experiment 2 58 4.2.1 Test Results and Discussion 58 Chapter 5. CONCLUSION 62 5.1 Major Findings and Pedagogical Implication 62 5.2 Limitations and Suggestions 65 REFERENCES 66 APPENDICES 77 ABSTRACT IN KOREAN 79Maste

Focusing on the relationship among Type A, stress and genetic risk score

학위논문(박사) -- 서울대학교대학원 : 인문대학 협동과정 인지과학전공, 2022. 8. 김홍기.고혈압은 대표적인 복합질환으로서 95% 이상이 특별한 원인이 없는 본태성으로, 유전적 영향과 생활 습관과 같은 환경적 요인이 복합적으로 작용하여 발생한다. 30세 이상 한국인의 고혈압 유병률은 2019년을 기준으로 약 30%에 달하며, 고혈압이 관상동맥질환, 뇌혈관질환, 심부전, 신장질환 등 많은 합병증을 유발하는 것을 고려하면 사전에 고혈압을 예방하는 것이 특히 중요하다고 할 수 있다. 고혈압의 발병에는 유전적 원인 외에도 식습관이나 운동과 같은 생활 습관 및 사회심리적 스트레스도 영향을 미치는 것으로 알려져 있다. 그렇다면 스트레스를 자주, 쉽게 인지하는 성격적인 특징도 이에 관여할 수 있다고 추정할 수 있으나, 이러한 주요 요인들 간의 인과 관계 및 유전적 요인과의 상호작용에 대해서는 연구가 많이 이루어 지지 않고 있다. 따라서 본 연구에서는 고혈압 발병에 영향을 주는 요인 중, 심리적으로 인지하는 스트레스와, 스트레스에 민감한 성격인 Type A를 중심으로 고혈압의 발병에 대한 영향력을 다각도로 분석하고 또한 고혈압의 예측 인자로서 가치가 있는지를 확인하였다. Type A는 시간에 대한 강박, 경쟁심, 적개심이 높은 성격 유형으로 분류되며, 스트레스에 민감하다고 알려져 있다. 본 연구는 질병청에서 2001년부터 격년으로 수집하고 있는 지역사회 기반 코호트의 임상 자료와 한국인 유전체 역학 조사 사업(KoGES)을 통해 수집된 이들의 유전체 자료를 사용하여, Type A와 스트레스 수준, 유전적 위험도를 통해 고혈압 발병에 대한 영향력을 단면(cross-section) 및 종단(longitudinal)으로 분석하였다. 먼저 단면적 자료를 통해 고혈압의 발병에 대한 Type A와 인지된 스트레스 수준, 그리고 이들을 매개할 것으로 추정한 비만(BMI)의 인과 구조를 구조방정식(structural equation modeling)으로 분석한 결과, 남녀 모두에서 Type A는 고혈압에 간접적인 효과만 관찰되었다. Type A는 인지된 스트레스 수준과 정적인(positive) 관계가 있었으며, 인지된 스트레스는 혈압에 정적으로 크게 영향을 미치는 BMI에 부적인(negative) 영향을 미쳤다. 이로 인해, 스트레스 수준이 높을수록 BMI 수준이 낮고, 혈압도 낮은 경향을 보였다. 이는 스트레스 수준이 높은 그룹이 낮은 그룹에 비해 음식 섭취량이 낮은 것과도 관련이 있는 것으로 보인다. 또한 2001년부터 2016년까지의 데이터로 Type A, 스트레스 수준, 유전적 위험도가 고혈압에 각각 미치는 영향과 이들의 상호작용을 분석한 콕스 (Cox) 회귀 분석에서는 유전적 위험도와 Type A만이 유의미하게 위험 비율을 높였으며, 이들의 상호작용은 관찰되지 않았다. 마지막으로 결정 나무 (Decision Tress) 및 그 확장 알고리즘인 랜덤 포레스트 (Random Forest)와 XGBoost를 통해 공변인과 유전적 위험도를 기본 모델로, Type A와 인지된 스트레스를 추가하며 예측 모델의 성능 개선도를 분석하였다. 개선 여부의 지표는 AUC뿐 아니라 재분류 (Reclassification) 방법인 NRI (Net Reclassification Improvements)와 IDI (Integrated Discrimination Index)를 사용하였으며, XAI의 한 종류인 SHAP value를 통해 feature importance를 계산하였다. 그 결과, 전반적으로 여성 데이터에서의 예측 성능이 좋았으며, Type A를 추가했을 때 성능 개선도가 가장 높았다. 남성 데이터에서는 Type A와 인지된 스트레스를 모두 추가하였을 때 개선이 있었다. SHAP value의 분포에서는 여성 데이터의 경우 Type A의 기여도가 높았으며, 인지된 스트레스는 혼재되어 있어 예측을 방해하는 것으로 나타났다. 남성 데이터는 인지된 스트레스가 Type A보다 기여도가 조금 더 높았다. 결국 생존 분석에서 유의미한 변수였던 유전적 위험도와 Type A가 좋은 성능을 보이는 예측 모델에서 유의미하게 사용되고 있으며, 예측 모델의 성과가 좋지 않은 경우에는 이를 따르지 않은 것을 확인할 수 있었다. 이를 통해, 단면적으로는 Type A 성격이 고혈압에 간접적으로 부정적인 영향을 주지만 장기적으로는 고혈압 발병에 있어 유전적 위험도만큼 이나 유의미한 영향을 미친다는 것을 알 수 있으며, 예측 모델에서도 유의미하게 기여하는 것을 확인하였다. 본 연구를 통해 성격과 스트레스, 비만과 혈압에 대한 인과 구조의 한 부분을 확인할 수 있었으며, 이는 유전적인 수준에서의 예방뿐 아니라 행동 수준에서도 고혈압을 예방할 수 있는 맞춤형 제안의 근거로서 활용될 수 있다. 즉, 본 연구를 통해 복합 질환의 요인들 간의 관계를 이해할 뿐만 아니라, 성격에 따른 개인 맞춤형 의료의 발전에도 기여하는 바가 있을 것으로 사료된다.In this study, Type A, stress level, genetic The influence on the development of hypertension through risk was analyzed by cross-section and longitudinal. First, through cross-sectional data, Type A and perceived stress levels for the onset of hypertension, and the causal structure of obesity (BMI) estimated to mediate them, were analyzed by structural equation modeling. As a result, Type A in both men and women was observed only as an indirect effect on hypertension. Type A had a positive relationship with perceived stress level, and perceived stress had a negative effect on BMI, which had a significant positive effect on blood pressure. As a result, the higher the stress level, the lower the BMI level and the lower the blood pressure. This seems to be related to the lower food intake in the high-stress group compared to the low-stress group. Also, in Cox regression analysis, which analyzed the effects of Type A, stress level, and genetic risk on hypertension with data from 2001 to 2006, and their interaction, only genetic risk and Type A were significantly risky. ratio was increased, and their interaction was not observed. Finally, through Decision Trees and its extension algorithms, Random Forest and XGBoost, covariates and genetic risk are used as basic models, Type A and perceived stress are added to improve the performance of the predictive model. analyzed. As a result, overall predictive performance in female data was good, and the performance improvement was the highest when Type A was added. In the male data, there was an improvement when both Type A and perceived stress were added. In the distribution of feature importance through SHAP, a method of XAI, the contribution of Type A was high in the case of female data, and the perceived stress was mixed, preventing prediction. For male data, perceived stress contributed slightly more than Type A. In the end, it was confirmed that the genetic risk and Type A, which were significant variables in the survival analysis, were used significantly in the predictive model with good performance, and did not follow when the predictive model did not perform well. Through this, it can be seen that, in cross-section, Type A personality indirectly negatively affects hypertension, but in the long term, it has a significant effect as much as the genetic risk in the development of hypertension, and it is confirmed that it contributes significantly in the predictive model. . Through this study, it was possible to identify a part of the causal structure of personality, stress, obesity and blood pressure, which can be used as a basis for a customized proposal to prevent hypertension not only at the genetic level but also at the behavioral level. That is, through this study, it is possible to understand the relationship between the factors of complex diseases and to contribute to the development of personalized medicine according to personality.Chapter 1. Introduction １ 1.1. Study Background １ 1.2. Questions and Purpose of the Research ６ 1.3. Methodologies and Organization １７ Chapter 2. Methods １８ 2.1. Community cohort data of Korean genome research project １９ 2.2. Measurements and Statistical Analysis ２１ 2.3. The inference of the causal structure among non-genetic psychological relevant risk factors ２５ 2.4. Genetic risk factors through weighted genetic risk score from GWAS ３０ 2.5. Interaction of Perceived Stress and Type A on wGRS ３５ 2.6. The evaluation of the contribution of Type A and Perceived Stress on Hypertension prediction ４１ Chapter 3. Results ４８ 3.1. Baseline characteristics of the data ４８ 3.2. GWAS and wGRS for hypertension ５１ 3.3. Causal structure inference of hypertension risk factors through structural equation model ５４ 3.4. Survival analysis ６１ 3.5. The Contribution of Perceived Stress and Type A ７３ Chapter 4. Discussion ８１ 4.1. Causal structure of psychosocial factors involved in the onset of hypertension ８２ 4.2. Interaction of genetic and psychosocial factors from a long-term perspective ８５ 4.3. Relevance of Type A and Stress as Predictors of Hypertension ８７ Chapter 5. Conclusion & Limitations ９１ Bibliography ９３ 국문초록 １０３ Appendix １０６박