• 한국음향학회지
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• 제32권5호
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• pp.438-445
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• 2013

본 논문은 일본어 음성인식기 신규 개발을 위해 초기에 부족한 일본어 음성데이터를 보완하는 방법이다. 일본어 발음과 한국어 발음이 유사한 특성을 근거로 한국어 음성 데이터를 이용한 일본어 음향모델 성능개선 방법에 대하여 기술하였다. 이종언어 간 음성 데이터를 섞어서 훈련하는 방법인 Cross-Language Transfer, Cross-Language Adaptation, Data Pooling Approach등 방법을 설명하고, 각 방법들의 시뮬레이션을 통해 현재 보유하고 있는 일본어 음성데이터 양에 적절한 방법을 선정하였다. 기존의 방법들은 훈련용 음성데이터가 크게 부족한 환경에서의 효과는 검증되었으나, 목적 언어의 데이터가 어느 정도 확보된 상태에서는 성능 개선 효과가 미비하였다. 그러나 Data Pooling Approach의 훈련과정 중 Tyied-List를 목적 언어로만으로 구성 하였을 때, ERR(Error Reduction Rate)이 12.8 %로 성능이 향상됨을 확인하였다.

• 영어영문학
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• 제59권4호
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• pp.593-617
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• 2013

Tales from Shakespeare, written by Charles and Mary Lamb in 1807, is an adaptation of Shakespeare's plays which was intended for children. Shakespeare's poetic language is transmitted into prose, which enables children to easily read his works. Charles and Mary Lamb collaborated in adapting Shakespeare's plays, but they undertook separate duties which revealed different attitudes in their approach to the adaptation. This dissertation examines Mary Lamb's adaption of Shakespeare's problem play All's Well That Ends Well and Charles Lamb's adaption of Shakespeare' tragedy King Lear, with an adapted pattern focusing on the plot and character. Charles Lamb stressed the "imagination of a fairy tale," which was against the trend in children's literature of the time, while Mary Lamb stressed "the moral and didactic element." Mary Lamb was concerned with the education of female children in the early nineteenth-century. As a result, the Tales presents "a double movement" or perspective, which stresses didactic elements, as well as imagination. These ambivalent attitudes caused critical debates in the nineteenth-century. However, the Lambs defended criticism against "the double movement," suspecting themselves to be "no bigger than a child," from the viewpoint of "the imagination," and reading the Tales to be effective at "making a child a virtuous man," from the viewpoint of "an education."

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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• pp.239-244
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• 2023

신경망 기반의 다국어 및 교차 언어 정보 검색 모델은 타겟 언어로 된 학습 데이터가 필요하지만, 이는 고자원 언어에 치중되어있다. 본 논문에서는 이를 해결하기 위해 영어 학습 데이터와 한국어-영어 병렬 말뭉치만을 이용한 효과적인 다국어 정보 검색 모델 학습 방법을 제안한다. 언어 예측 태스크와 경사 반전 계층을 활용하여 인코더가 언어에 구애 받지 않는 벡터 표현을 생성하도록 학습 방법을 고안하였고, 이를 한국어가 포함된 다국어 정보 검색 벤치마크에 대해 실험하였다. 본 실험 결과 제안 방법이 다국어 사전학습 모델과 영어 데이터만을 이용한 베이스라인보다 높은 성능을 보임을 실험적으로 확인하였다. 또한 교차 언어 정보 검색 실험을 통해 현재 검색 모델이 언어 편향성을 가지고 있으며, 성능에 직접적인 영향을 미치는 것을 보였다.

• 한국컴퓨터정보학회논문지
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• 제27권11호
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• pp.241-249
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• 2022

본 연구는 다문화청소년패널연구 2기 데이터를 활용하여 다문화 아동들의 심리사회 적응, 이중문화체험, 부모지지 및 양육태도, 학교생활이 한국어 능력 발달에 미치는 영향을 구조방정식 모형으로 분석하고 검증하는 것이다. 연구 대상은 외국인 가정과 중도입국 가정의 396명으로 2019년도에 초등학교 4학년에 재학하고 있었던 다문화 아동들이다. 연구 결과 심리사회 적응, 이중문화체험, 학교 활동은 다문화 아동들이 한국어를 구사하고 이해하는 능력에 직·간접적으로 의미있는 영향을 미치는 것으로 나타났다. 특히, 학교 활동이 다문화 아동들의 한국어 능력 향상에 직접 영향을 미치는 것으로 나타나 친구의 지지와 교사의 지지가 교육 현장의 교육활동에서 매우 중요한 부분으로 다루어져야 한다는 것을 파악하였다. 이러한 결과는 다문화 아동을 위한 한국어 교육정책에서 한국어 능력 발달에 영향을 미치는 가장 이상적인 교육 환경이 필수적으로 반영되어야 한다는 것을 의미한다.

• 디지털융복합연구
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• 제16권11호
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• pp.511-520
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• 2018

본 연구에서는 외국인 유학생의 성격강점이 대학생활적응에 영향을 미치는지 살펴보고, 문화적응스트레스가 매개효과를 가지는지를 파악하고자 하였다. 이를 위해 선행연구를 바탕으로 연구 모형을 설정하고, G시와 N시에 소속된 외국인 유학생 263명을 대상으로 조사를 실시하고, spss 통계 프로그램을 활용하여 자료를 분석하였다. 연구결과, 외국인 유학생의 성격강점은 대학생활적응에 영향을 미치고 있었으며, 외국인 유학생의 문화적응스트레스는 성격강점과 대학생활적응 간의 관계를 부분 매개하는 것으로 나타났다. 따라서 문화적응스트레스를 감소시키는 프로그램을 개발하고, 외국인 유학생들의 대학생활 적응을 위한 지속적인 상담과 전문상담사를 대학 내에 두는 것이 필요함을 제안하였다.

• 대한물리의학회지
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• 제10권3호
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• pp.47-55
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• 2015

PURPOSE: Stoke is one of most common disabling conditions and it is still lacking of measuring patient's functioning level. The aim of the study was to develop Korean language version of stroke impact scale 3.0. METHODS: Korean version of stroke impact scale 3.0 was developed in idiomatic modern Korean with a standard protocol of multiple forward and backward translations and an expert reviews to achieve equivalence with the original English version. Interviews with clinicians who were currently managing patients with stroke were also conducted for language evaluation. A reliability test was performed to make final adaptation using a pre-final version. To assess the reliability of the translated questionnaire, the intraclass correlation coefficient (ICC) was calculated for each domain of the scale. RESULTS: Thirty subjects (16 male, 14 female) aged from 20 to 75 years old participated to review the translated questionnaire. Reliability of each domain of the questionnaire was found to be good in strength (ICC=0.74), ADL (ICC=0.81), mobility (ICC=0.90), hand function (ICC=0.80) and social participation (ICC=0.79), communication (ICC=0.77) with total (ICC=0.76). However, domains of memory and thinking (ICC=0.66), and emotion (ICC=0.27) and showed poor reliability. CONCLUSION: This study indicates that the Korean version of SIS 3.0 was successfully developed. Future study needed for obtaining the validity of the Korean version of SIS 3.0.

• 대한임베디드공학회논문지
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• 제19권2호
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• pp.73-81
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• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• 통상정보연구
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• 제12권3호
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• pp.145-166
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• 2010

Chinese employees in Korea have been the leading workers, about 260,000 of 700,000(3% of total employees), in our foreigner's job market. The corporate cultural adaptation of Chinese people is very important to the corporate productivity as well as the Korea economy. The objectives of this paper are to compare the corporate cultural adaptation and job performance of Chinese employees in Korea and to propose the efficient business policies for firm employing Chinese. The propositions could be summarized that language skills and pre-training are positive to the corporate cultural adaptation. This adaptation improved the job performance as a role of motivators in their firms. The job satisfaction and job involvement based on the corporate cultural adaptation are positive relationship to the job performance.

• 대한음성학회지:말소리
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• 제46호
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• pp.117-126
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• 2003

This paper presents our language model adaptation for Korean spontaneous speech recognition. Korean spontaneous speech is observed various characteristics of content and style such as filled pauses, word omission, and contraction as compared with the written text corpus. Our approaches focus on improving the estimation of domain-dependent n-gram models by relevance weighting out-of-domain text data, where style is represented by n-gram based tf/sup */idf similarity. In addition to relevance weighting, we use disfluencies as Predictor to the neighboring words. The best result reduces 9.7% word error rate relatively and shows that n-gram based relevance weighting reflects style difference greatly and disfluencies are good predictor also.

• ETRI Journal
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• 제36권3호
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• pp.429-438
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• 2014

Semantic role labeling (SRL) is a task in natural-language processing with the aim of detecting predicates in the text, choosing their correct senses, identifying their associated arguments, and predicting the semantic roles of the arguments. Developing a high-performance SRL system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Constructing SRL training data for a new domain is very expensive. Therefore, domain adaptation in SRL can be regarded as an important problem. In this paper, we show that domain adaptation for SRL systems can achieve state-of-the-art performance when based on structural learning and exploiting a prior model approach. We provide experimental results with three different target domains showing that our method is effective even if training data of small size is available for the target domains. According to experimentations, our proposed method outperforms those of other research works by about 2% to 5% in F-score.