한국엔터테인먼트산업학회논문지 (Journal of Korea Entertainment Industry Association)

  • 제15권4호
  • /
  • Pages.15-29
  • /
  • 2021
  • /
  • 1976-6211(pISSN)
  • /
  • 2384-017X(eISSN)
한국엔터테인먼트산업학회 (The Korea Entertainment Industry Association)
권호 표지
DOI QR코드

DOI QR Code

A.I.에이전트와의 보이스 인터랙션 : 국내외 IT회사 사례연구

Voice Interactions with A. I. Agent : Analysis of Domestic and Overseas IT Companies

  • Lee, Seo-Young (Division of Media, North Seoul Campus, DongYang University)
  • 투고 : 2021.05.17
  • 심사 : 2021.06.25
  • 발행 : 2021.06.30
⟨ 이전 논문 다음 논문 ⟩

초록

인공지능 에이전트는 4차 산업혁명의 핵심 기술이고, 현재 많은 기업들이 AI 음성 인식 비서를 탑재 출시함으로써 산업 내 치열한 경쟁을 벌이고 있다. 애플, 마이크로소프트, 구글, 아마존, 삼성 등 고객 충성도를 확보하고 있으며 자사 하드웨어 제품을 내놓고 있는 기업의 경우, AI 비서 서비스를 자사 제품에 적용함으로써 고객 충성도를 높이고, 시장 점유율 역시 극대화뿐 아니라 향후 음성 인터페이스 플랫폼 시장 장악력을 확대하고 있다. 본 연구는 인공지능분야의 해외 및 국내 주요 기업들의 현황을 분석하고 보이스 UI 개발과 혁신 수용 관점에서 사용자 만족을 위한 기술 발전 방향에 초점을 맞추어 미래 전략 방향을 제언했다. B2B 기술적인 측면에서는 음성 인식률을 높이고 하드웨어향상, 자연언어 처리기술 및 빅데이터 및 인공지능 접목한 혁신 기술의 데이터가 쌓인 클라우드 컴퓨팅 활용뿐 아니라 및 Open A.I.언어 인공지능인 GPT-3의 활용 및 사용성, 유용성, 감성 측면에서 사용자 만족을 높일 필요가 있다. 본 연구는 산업계와 학계에 실무적, 이론적 함의를 준다.

Many countries and companies are pursuing and developing Artificial intelligence as it is the core technology of the 4th industrial revolution. Global IT companies such as Apple, Microsoft, Amazon, Google and Samsung have all released their own AI assistant hardware products, hoping to increase customer loyalty and capture market share. Competition within the industry for AI agent is intense. AI assistant products that command the biggest market shares and customer loyalty have a higher chance of becoming the industry standard. This study analyzed the current status of major overseas and domestic IT companies in the field of artificial intelligence, and suggested future strategic directions for voice UI technology development and user satisfaction. In terms of B2B technology, it is recommended that IT companies use cloud computing to store big data, innovative artificial intelligence technologies and natural language technologies. Offering voice recognition technologies on the cloud enables smaller companies to take advantage of such technologies at considerably less expense. Companies also consider using GPT-3(Generative Pre-trained Transformer 3) an open source artificial intelligence language processing software that can generate very natural human-like interactions and high levels of user satisfaction. There is a need to increase usefulness and usability to enhance user satisfaction. This study has practical and theoretical implications for industry and academia.

키워드

과제정보

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2020S1A5A8041958)

참고문헌

  1. Lee, H. S., & Kim, P. S.(2019). The effect of consumers' technology acceptance and resistance on the intention to use artificial intelligence. Business Administration Research, 48(5): 1195-1219.
  2. Park, S. A., & Choi, S. J.(2018). Factors affecting satisfaction with artificial intelligence speakers and intention to continue use: Focusing on functional and emotional factors. Information Society and Media, 19(3): 159-182. https://doi.org/10.52558/ISM.2018.12.19.3.159
  3. Lee, E. G.(2020). A study on acceptance of voice recognition-based virtual assistant service: Application of UTAUT model. Research on Merchandise Studies, 38(5): 111-120.
  4. Kang J. M., & Park J. H.(2016). Research trend of artificial intelligence service based on voice recognition. The Journal of Information and Communication Sciences, 17(1): 50-56.
  5. Seo J. I.(2017). Intelligent virtual assistant service trend and prospect. KISTI Information Analysis Report, 47: 1-48.
  6. Kim S. H.(1994). The current status and prospect of practical use of speech recognition technology. Journal of the Acoustical Society of Korea, 13(2): 86-95.
  7. Park, J. H., Yoon, K. G., & Min, S. T.(2019). Technology trend of chatbot system based on artificial intelligence. Journal of Information Processing Society, 26(2): 39-46.
  8. Yoo J., Oh J. Y., & Kim Y. J.(2005). Implementation of web services for authentication and speech recognition in mobile environments. Journal of Multimedia Society, 8(2): 225-232.
  9. Yang H. T.(2017). A study on consumer acceptance of virtual personal assistant devices: focused on the perceived value of users. Journal of the Korea Contents Association, 17(10): 179-189. https://doi.org/10.5392/JKCA.2017.17.10.179
  10. Liu, F., Zhao, X., Chau, P. Y., & Tang, Q.(2015). Roles of perceived value and individual differences in the acceptance of mobile coupon applications. Internet Research, 25(3): 471-495. https://doi.org/10.1108/IntR-02-2014-0053
  11. Kim, H. Y., Lee, J. Y., Mun, J. M., & Johnson, K. K.(2017). Consumer adoption of smart in-store technology: Assessing the predictive value of attitude versus beliefs in the technology acceptance model. International Journal of Fashion Design Technology Education, 10(1): 26-36. https://doi.org/10.1080/17543266.2016.1177737
  12. Hwang, S., Kim, J., Park, E., & Kwon, S. J.(2020). Who will be your next customer: A machine learning approach to customer return visits in airline services. Journal of Business Research, 121: 121-126. https://doi.org/10.1016/j.jbusres.2020.08.025
  13. Chung, J., & Tan, F. B.(2004). Antecedents of perceived playfulness: An exploratory study on user acceptance of general information searching websites. Information and Management, 41(7): 869-881. https://doi.org/10.1016/j.im.2003.08.016
  14. Lee, D. Y., & Lehto, M. R.(2013). User acceptance of YouTube for procedural learning: An extension of the technology acceptance model. Computer Education, 61: 193-208. https://doi.org/10.1016/j.compedu.2012.10.001
  15. Kwon, S. J., Park, E., & Kim, K. J.(2014). What drives successful social networking services? A comparative analysis of user acceptance of Facebook and Twitter. The Social Science Journal, 51(4): 534-544. https://doi.org/10.1016/j.soscij.2014.04.005
  16. Park, E., & Kwon, S. J.(2016). The adoption of teaching assistant robots: a technology acceptance model approach. Program, 50(4): 354-366. https://doi.org/10.1108/PROG-02-2016-0017
  17. Cha, K., & Kwon, S. J.(2018). Understanding the adoption of e-learning in South Korea: Using the extended Technology Acceptance Model approach. KEDI Journal of Educational Policy, 15(2): 167-185.
  18. Park, E., Kim, S., Kim, Y., & Kwon, S. J.(2018). Smart home services as the next mainstream of the ICT industry: Determinants of the adoption of smart home services. Universal Access in the Information Society, 17(1): 175-190. https://doi.org/10.1007/s10209-017-0533-0
  19. Bradford, M., & Florin, J.(2003). Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems. International Journal of Accounting Information Systems, 4(3): 205-225. https://doi.org/10.1016/S1467-0895(03)00026-5
  20. Lee, I., & Lee, K.(2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4): 431-440. https://doi.org/10.1016/j.bushor.2015.03.008
  21. Shin, D. H., Hwang, Y., & Choo, H.(2013). Smart TV: Are they really smart in interacting with people? Understanding the interactivity of Korean smart TV. Behaviour & Information Technology, 32(2): 156-172. https://doi.org/10.1080/0144929X.2011.603360
  22. Whitmore, A., Agarwal, A., & Da Xu, L.(2015). The Internet of Things: A survey of topics and trends. Information Systems Frontiers, 17(2): 261-274. https://doi.org/10.1007/s10796-014-9489-2
  23. Kim, Y. H., Kim, D. J., & Wachter, K.(2013). A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention. Decision Support System, 56: 361-370. https://doi.org/10.1016/j.dss.2013.07.002
  24. Park, E., del Pobil, A. P., & Kwon, S. J.(2018). The Role of Internet of Things(IoT) in Smart Cities. Sustainability, 10(5): 1388-1398. https://doi.org/10.3390/su10051388
  25. Kwon, S. J., Ryu, D., & Park, E.(2018). The influence of entrepreneurs' strategic agility and dynamic capability on the opportunity pursuit process of new ventures: evidence from South Korea. Academy of Strategic Management Journal, 17(1): 1-17.
  26. Lee, S. Y., & Choi, J.(2017). Enhancing user experience with conversational agent for movie recommendation: Effects of self-disclosure and reciprocity. International Journal of Human-Computer Studies, 103: 95-105. https://doi.org/10.1016/j.ijhcs.2017.02.005
  27. Olsen, S. O.(2002). Comparative evaluation and the relationship between quality, satisfaction, and repurchase loyalty. Journal of the Academy of Marketing Science, 30(3): 240-249. https://doi.org/10.1177/0092070302303005
  28. Heo, D. H., & Park, J. R.(2021). A Study on the audio mastering results of artificial intelligence and human experts. Journal of the Korea Entertainment Industry Association,15(3): 41-50. https://doi.org/10.21184/jkeia.2021.4.15.3.41
  29. Yoo, T. K.(2021). Film production using artificial intelligence with a focus on visual effects. Journal of the Korea Entertainment Industry Association, 15(1): 53-62. https://doi.org/10.21184/jkeia.2021.1.15.1.53