• Journal of Technology Innovation
• /
• v.27 no.4
• /
• pp.111-144
• /
• 2019

As virtual assistants rapidly diffused into the market, the voice shopping market is expected to expand. The purpose of this study is to identify the factors that determine the consumers' intention to adopt voice shopping by using the unified theory of acceptance and use of technology(UTAUT). In this study, we set variables that influence the intention to adoption of voice shopping with performance expectation and effort expectations as the variables of UTAUT and playfulness expectations as an extended variable. In addition, we also include four voice secretary attributes such as response accuracy, compatibility, social presence, and safety in our research model to investigate the source of motivation of voice shopping adoption. The result of this analysis shows that variables such as performance expectation, effort expectation, and amusement expectation have a positive effect on the intention to adoption of voice shopping. With respect to the four voice shopping attributes, compatibility had a positive effect on performance expectancy, effort expectancy, and playfulness expectancy. Social presence has a positive effect on playfulness expectancy. Safety has a positive effect on effort expectancy and playfulness expectancy. On the other hand, response accuracy is not significant for performance expectancy, effort expectancy, and playfulness expectancy. This study reveals the determinants of intention to adopt the new purchasing method called voice shopping, and suggests the important factors for the innovation of commerce business.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.6
• /
• pp.187-194
• /
• 2011

The purpose of this study was to analyze the effects of internal marketing on job satisfaction and organizational commitment of secretaries working in IT based companies. Especially, to analyze the effects of internal marketing on secretaries in IT companies, this study has adopted job specialization rather than the comprehensive market point of internal customers. Through the analysis, the following results were obtained: firstly, internal marketing factors such as effectiveness of communication, various compensation systems, and chance of educational training have positive effects on job satisfaction and organizational commitment. Secondly, job satisfaction has no impact on organizational commitment. To be able to satisfy external customers through internal marketing, communication skills has be to improved between the workers in the company, and also various compensation systems and educational training should be provided more extensively. The secretary in the company is considered a vital link between the company and customer service. In this view, the result of this study is expected to provide some managerial strategies to decision maker in the company to establish a way to increase the satisfaction and needs of internal customers in applying internal marketing.

• Environmental engineer
• /
• v.23 s.233
• /
• pp.3-9
• /
• 2006

"환경과 경제는 상호 보완적이면서 상생하는 정책을 수립해야 합니다. 임기동안 그 중심에서 임무를 충실히 수행할 예정입니다." 염태영 청와대 환경비서관은 현실에 봉착된 환경문제를 지혜롭게 해결하는 것이 급선무라고 말한다. 그는 오랫동안 시민단체에서 환경을 보호하는 목소리를 높이다가 지난해 1월에 환경관련 현안들을 조정하는 청와대 환경비서관직에 부임했다. 다음은 염 비서관과의 인터뷰 내용이다.

• Digital Contents
• /
• no.10 s.161
• /
• pp.122-125
• /
• 2006

휴대전화는 동전의 양면과 같다. 야누스의 얼굴을 가졌다. 삶의 질을 높여줬다고도 하고 삶의 질을 떨어뜨렸다고도 한다. 휴대전화는 아내와 같다. 없으면 불편하고 있으면 노예가 된다. 하루가 멀다고 신기술을 탑재한 세련된 디자인의 휴대전화들이 쏟아져 나온다. 휴대전화의 진화는 눈부시다. 음성통화가 전부였던 초창기와는 다르게 이제는 개인비서이자 생활필수품이다. 몸의 연장이요, 내 손안의 세상이다.

• Annual Conference on Human and Language Technology
• /
• 2013.10a
• /
• pp.18-23
• /
• 2013

기존 대화시스템과 달리 대화형 개인 비서 시스템은 사용자에게 정보를 제공하기 위해 앱(APP)을 구동하는 방법을 사용한다. 사용자가 앱을 통해 정보를 얻고자 할 때, 사용자가 필요로 하는 정보를 제공해주기 위해서는 사용자의 목적을 정확하게 인식하는 작업이 필요하다. 그 작업 중 중요한 두 요소는 개체명 인식과 문장목적 인식이다. 문장목적 인식이란, 사용자의 문장을 분석해 하나의 앱에 존재하는 여러 정보 중 사용자가 원하는 정보(문장의 목적)가 무엇인지 찾아주는 인식작업이다. 이러한 인식시스템을 구축하는 방법 중 대표적인 방법은 사전규칙방법과 기계학습방법이다. 사전규칙은 사전정보와 규칙을 적용하는 방법으로, 시간이 지남에 따라 새로운 규칙을 추가해야하는 문제가 있으며, 규칙이 일반화되지 않을 경우 오류가 증가하는 문제가 있다. 또 두 인식작업을 파이프라인 방식으로 적용 할 경우, 개체명 인식단계에서의 오류를 가지고 문장목적 인식단계로 넘어가기 때문에 두 단계에 걸친 성능저하와 속도저하를 초래할 수 있다. 이러한 문제점을 해결하기 위해 우리는 통계기반의 기계학습방법인 Conditional Random Fields(CRF)를 사용한다. 또한 사전정보를 CRF와 결합함으로써, 단독으로 수행하는 CRF방식의 성능을 개선시킨다. 개체명과 문장목적인식의 구조를 분석한 결과, 비슷한 자질을 사용할 수 있다고 판단하여, 두 작업을 동시에 수행하는 방법을 제안한다. 실험결과, 사전규칙방법보다 제안한 방법이 문장단위 2.67% 성능개선을 보였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.17-18
• /
• 2019

최근 4차 산업혁명의 핵심 분야 중 하나인 인공지능에 대한 많은 연구가 이루어지고 있다. 많은 기업들이 인공지능 스피커와 같은 제품을 출시하고 있으나 대부분 비서 역할만을 할 수 있도록 구성된 제품이 대부분이다. 그러나 학교와 같이 많은 사람이 존재하는 경우 시끄러운 환경에서 사용되고 있는 인공지능 스피커는 명령 인식이 제대로 되지 않아 실용도가 저하되는 단점을 가지고 있으며, 현재 인공지능 스피커는 단순한 질의응답 수준의 응대만 가능하여 다소 부족한 부분이 있다. 또한 인공지능의 급속한 발전으로 인공지능 스피커가 아닌 전자제품에 인공지능 비서 기능이 탑재된 제품도 새롭게 출시되어 인공지능 스피커가 필요 없을 수도 있기에, 본 논문에서는 학교와 같은 주변의 소음이 많이 발생하는 교육 환경에서도 소통이 가능한 인공지능 마이크를 활용할 수 있는 모델을 제안한다.

• Electronics and Telecommunications Trends
• /
• v.36 no.1
• /
• pp.1-11
• /
• 2021

In this study, we introduce trends in and the future of digital personal assistants. Recently, digital personal assistants have begun to handle many tasks like humans by communicating with users in human language on smart devices such as smart phones, smart speakers, and smart cars. Their capabilities range from simple voice commands and chitchat to complex tasks such as device control, reservation, ordering, and scheduling. The digital personal assistants of the future will certainly speak like a person, have a person-like personality, see, hear, and analyze situations like a person, and become more human. Dialogue processing technology that makes them more human-like has developed into an end-to-end learning model based on deep neural networks in recent years. In addition, language models pre-trained from a large corpus make dialogue processing more natural and better understood. Advances in artificial intelligence such as dialogue processing technology will enable digital personal assistants to serve with more familiar and better performance in various areas.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.287-310
• /
• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• Management & Information Systems Review
• /
• v.33 no.5
• /
• pp.261-283
• /
• 2014

The aim of this study is to examine the relationships between emotional labor of surface acting and deep acting along with job satisfaction and turnover intention. Furthermore, the study attempts to understand the moderating effects of resilience on adjustment in regards to the emotional labor, surface acting and deep acting, and job satisfaction and turnover intention. For this study, a survey was conducted among administrative assistants and five hypotheses were verified. The findings of this research are summarized as follows: First, the surface acting of emotional labor has a statistically significant positive correlational effect on turnover intentions. Second, the deep acting of emotional labor has a statistically significant negative correlational effect on turnover intentions. Third, the surface acting of emotional labor has a statistically significant negative correlational effect on job satisfaction. Fourth, the deep acting of emotional labor has a statistically significant positive correlational effect on job satisfaction. Fifth, there is a moderating effect of resilience between the deep acting of emotional labor and job satisfaction. This study is meaningful in that it helps understand the relationship between the administrative assistants' emotional labor, resilience, turnover intention, and job satisfaction and that it proposes implications on vitalizing organizational communication and emotional programs.

• Annual Conference on Human and Language Technology
• /
• 2018.10a
• /
• pp.364-366
• /
• 2018

Visual Question Answering(VQA)은 주어진 이미지와 질문에 대해 알맞은 정답을 찾는 기술이다. VQA는 어린이 학습, 인공지능 비서 등 여러 분야에 활용할 수 있는 중요한 기술이다. 그러나 관련된 한국어 데이터를 확보하기 힘든 이유로 한국어를 이용한 연구는 이루어지지 못하고 있다. 본 논문에서는 기존 영어 VQA 데이터를 한글로 번역하여 한국어 VQA 데이터로 사용하며, 이미지 정보와 질문 정보를 적절히 조절할 수 있는 Gate를 한국어 VQA에 적용한다. 실험 결과, 본 논문에서 제안한 모델이 영어 및 한국어 VQA 데이터에서 다른 모델보다 더 좋은 성능을 보였다.