• Asia Marketing Journal
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• 제22권3호
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• pp.87-105
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• 2020

With the development of Information Technology, customers require promptly higher quality products and services. Companies try to make newly digital marketing strategies, but there are no empirical researches on them. This article empirically presents a new perspective that companies can shape the customer decision journey ahead by coordinating customer experience. In this article, based on Elaborated Likelihood Model (ELM) theory, customer experience consists of the emotional or cognitive experience. We surveyed about 200 subjects (N = 217) in their 20s and 30s based on the International Music Industry Association's Music Listening 2019 report, then analyzed four different models (before personalization-cognitive experience, before personalization-emotional experience, after personalization- cognitive experience, after personalization-emotional experience) by JASP and R Studio. We conducted Structural Equation Model (SEM) and paired t-test. Personalization factors are about recommendation systems in Spotify. The results of survey represent that companies can shape the Customer Decision Journey (CDJ) ahead especially through enhance cognitive experience. It empirically proves Elaborated Likelihood Model (ELM). The conclusion can be drawn that 'pulling' customer experience can be a new marketing strategies in the digital era.

• 한국문헌정보학회지
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• 제40권3호
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• pp.53-71
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• 2006

본 연구는 독서교육 프로그램의 유형과 독서방식에 따라 창의력과 자기주도적 학습능력이 어떻게 나타나는지 그리고 교육 기간에 따라 창의력과 자기주도적 학습능력에 미치는 영향에는 어떠한 차이가 있는지를 파악하기 위한 것이다. 2005년 4월부터 12월까지 초등학교 6학년 2개 반을 대상으로 한 반은 쓰기 중심 독서프로그램 모형인 'Author-Reader-Inquirer Cycle'을 실시하고, 다른 한 반은 말하기 듣기 프로그램중심 독서프로그램 모형인 'Literature Circles'를 실시하였다. 창의력과 자기주도적 학습능력을 검증하기 위해 사전 1회차 검사, 7월에 단기 교육 사후검사. 2학기말인 12월에 장기 교육 사후검사를 실시하였다. 연구 결과 독서교육은 어린이들의 창의력과 자기주도적 학습능력을 향상시키는 것으로 나타났다. 또한 쓰기 중심의 독서교육 프로그램이 말하기 듣기 프로그램에 비해 효과적이고, 단기 독서교육 보다는 장기 독서교육이 효과적인 것으로 나타났으며, 독서 방식 중에서는 음독, 묵독, 다독, 통독, 발췌독에 비해 정독을 통한 독서방식이 창의력과 자기주도적 학습능력을 향상시킬 수 있는 것으로 나타났다.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2000년도 7월 학술대회지
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• pp.117-134
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• 2000

Kim, Key-Seop(2000). English Restructuring and A Use of Music in Teaching English Pronunciation. JSEP 2000 voU This study has two-fold aims: one is to clarify the restructuring of English in utterance, and the other is to relate it to teaching English pronunciation for listening and speaking with a use of music and song by suggesting a model of 10-15 minute pronunciation class syllabus for every period in class. Generally, English utterances are restructured by stress-timed rhythm, irrespective of syntactic boundaries. So the rhythmic units are arranged in isochronous groups, of which the making is to attach clitic(s) to a host or head often leftwards and sometimes rightwards, which results in linking, contraction, reduction, sound change and rhythm adjustment in utterance, just as in music and song. With English restructuring focused on, a model of English pronunciation class syllabus is proposed to be put forward in class for every period of a lesson or unit. It tries to relate the focused factor(s) in pronunciation to the integrated, with teaching techniques and music made use of.

• 영어어문교육
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• 제10권1호
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• pp.53-76
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• 2004

This paper introduces a class model based on a course, Internet English, offered by an English department at a university. The course has dual purposes of developing students I English skills and Internet using skills at the same time. In support of using the Internet for language learning, the advantages of project-based language learning and constructivist learning in relation to CALL are explored. The activities in this course, which are basically project-based under the paradigm of constructivist learning perspective, are explained in detail to show the relationship between second language learning theory and teaching application. The way how the four language skills - speaking, listening, reading, and writing - are integrated in this class is described as well. Finally, judgmental evaluation of the course by the students is noted. The results show that a project-based CALL class could be a promising class model to realize an integrative, constructivist, and authentic learning.

• 한국음향학회지
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• 제16권2호
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• pp.16-25
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• 1997

이 연구에서는, 반사 음파 전달 특성에 의한 공간감 효과를 이용하여 음상 정위를 개선할 수 있는 HRTF 모델링 방법을 제안하였다. 실험 결과, 최적으로 평가된 반사 음파 전달 특성을 갖는 HRTF 모델은, 직접 음파 전달 특성만으로 구성된 HRTF 모델과 비교하여 음상 전위가 약 23% 이상 개선되었다. 그리고, 적절한 공간감이 음상 정위의 정확도를 증가시킬 수 있는 요소임을 알았다.

• 한국음향학회지
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• 제31권1호
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• pp.39-50
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• 2012

A voice transformation (VT) method that can make the utterance of a source speaker mimic that of a target speaker is described. Speaker individuality transformation is achieved by altering three feature parameters, which include the LPC cepstrum, pitch period and gain. The main objective of this study involves construction of an optimal sequence of features selected from a target speaker's database, to maximize both the correlation probabilities between the transformed and the source features and the likelihood of the transformed features with respect to the target model. A set of two-pass conversion rules is proposed, where the feature parameters are first selected from a database then the optimal sequence of the feature parameters is then constructed in the second pass. The conversion rules were developed using a statistical approach that employed a maximum likelihood criterion. In constructing an optimal sequence of the features, a hidden Markov model (HMM) was employed to find the most likely combination of the features with respect to the target speaker's model. The effectiveness of the proposed transformation method was evaluated using objective tests and informal listening tests. We confirmed that the proposed method leads to perceptually more preferred results, compared with the conventional methods.

• International Journal of Internet, Broadcasting and Communication
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• 제13권1호
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• pp.161-167
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• 2021

This paper proposes a new personalized HRTF estimation method which is based on a deep neural network (DNN) model and improved elevation reproduction using a notch filter. In the previous study, a DNN model was proposed that estimates the magnitude of HRTF by using anthropometric measurements [1]. However, since this method uses zero-phase without estimating the phase, it causes the internalization (i.e., the inside-the-head localization) of sound when listening the spatial sound. We devise a method to estimate both the magnitude and phase of HRTF based on the DNN model. Personalized HRIR was estimated using the anthropometric measurements including detailed data of the head, torso, shoulders and ears as inputs for the DNN model. After that, the estimated HRIR was filtered with an appropriate notch filter to improve elevation reproduction. In order to evaluate the performance, both of the objective and subjective evaluations are conducted. For the objective evaluation, the root mean square error (RMSE) and the log spectral distance (LSD) between the reference HRTF and the estimated HRTF are measured. For subjective evaluation, the MUSHRA test and preference test are conducted. As a result, the proposed method can make listeners experience more immersive audio than the previous methods.

• 복식문화연구
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• 제23권5호
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• pp.793-806
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• 2015

This study is to explore the effect of music characteristics (i.e., likeliness and familiarity of music) on the relationship between mood and attitude toward the product in the online shopping mall selling hand-made shoes. A total of 319 consumers participated in experiments with online shopping mall stimuli with a variety of background music. In results, consumer mood positively affected attitude toward the hand-made shoe products in the online shopping mall under background music. A moderating effect of music likeliness was found in the relationship between mood and product attitude, indicating that mood more strongly affected product attitude under more liked music than under less liked music. When consumers are listening to more liked music and are in good mood, they may build their attitudes toward products independently from their mood, whereas they may build positive attitude under good mood versus negative attitudes under bad mood if they are listening to less liked music. A moderating effect of music familiarity was not found in the relationship between mood and product attitude. Based on results, it was confirmed that the S-O-R model could be applied to explain the effect of background music on consumer responses in online shopping malls. Marketers may be able to select and adjust the likeliness and familiarity of background music to better serve consumers in diverse shopping conditions, referring to the study findings.

• 한국음향학회지
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• 제40권2호
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• pp.176-182
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• 2021

본 논문은 다양한 손실 함수에 따른 Deep Nerual Network(DNN) 기반 음성 향상 모델의 성능을 비교 평가한다. 베이스라인 모델로는 음성의 위상 정보를 고려할 수 있는 복소 네트워크를 사용하였다. 손실 함수는 두 가지 유형의 기본 손실 함수, Mean Squared Error(MSE)와 Scale-Invariant Source-to-Noise Ratio(SI-SNR)를 사용하였으며 두 가지 유형의 지각 기반 손실 함수 Perceptual Metric for Speech Quality Evaluation(PMSQE)과 Log Mel Spectra(LMS)를 사용한다. 성능은 각 손실 함수의 다양한 조합을 사용하여 얻은 출력을 객관적인 평가와 청취 테스트를 통해 측정하였다. 실험 결과, 지각기반 손실 함수를 MSE 또는 SI-SNR과 결합하였을 때 전반적으로 성능이 향상되며, 지각기반 손실함수를 사용하면 객관적 지표에서 약세를 보이는 경우라도 청취 테스트에서 우수한 성능을 보임을 확인하였다.

• 한국콘텐츠학회논문지
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• 제15권3호
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• pp.21-31
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• 2015

본 논문에서는 기존에 연구되었던 Thayer의 인간의 감성 모델을 바탕으로 음악을 듣고 느끼는 감성을 8가지 감성으로 정의한 음악 감성모델로 제시하였다. 감성에 영향을 주는 음악의 요소는 음악의 템포, 역동성, 진폭변화, 밝기, 잡음 등 5가지로 선택하였다. 8가지 감성으로 이루어진 감성 모델에 따라서 8가지 감성으로 분류된 160곡의 노래를 선곡하여 실제 데이터를 추출하여 분석하였다. 실제 데이터의 분석을 통해 5가지 요소의 가중치로 이루어진 감성 수식을 도출하였고 임의의 음악에 대하여 감성 수식을 통해서 2차원 감성 좌표계에 매핑 하여 감성을 예측할 수 있도록 알고리즘을 설계하였다. 또한 2차원 감성 좌표계에서의 좌표 값을 이동시켜 감성을 제어할 수 있는 방법을 제시하였다.