Advertisement

Towards the Development of the Multilingual Multimodal Virtual Agent

  • Inese Vīra
  • Jānis Teseļskis
  • Inguna Skadiņa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8686)

Abstract

The mobile virtual agent (assistant) is one of today’s most intriguing new technologies. Development of such an agent is multidisciplinary work, and natural language processing is an indispensable part of this work. Our goal is to develop a multilingual multimodal virtual agent. In this paper, we describe the first steps towards this goal – the design, development, and evaluation of the intelligent translation agent. The agent provides speech to speech translation of words, phrases, and sentences from English into Spanish, French, or Russian. The initial evaluation performed for natural language components, as well as for the agent in general, indicated that there is user interest and that such an application is useful.

Keywords

intelligent virtual agent multimodal systems speech interfaces machine translation question answering multilingual information systems 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Urbina, J.: I Flirt and Tweet. Follow Me at #Socialbot. In: The New York Times (August 10, 2013), http://www.nytimes.com/2013/08/11/sunday-review/i-flirt-and-tweet-follow-me-at-socialbot.html?_r=0
  2. 2.
    Weizenbaum, J.: ELIZA – A Computer Program for the Study of Natural Language Communication between Man and Machine. In: Communications of the Association for Computing Machinery, vol. 9, pp. 36–45. ACM, New York (1966)Google Scholar
  3. 3.
    Paul, M., Okuma, H., Yamamoto, H., Sumita, E., Matsuda, S., Shimizu, T., Nakamura, S.: Multilingual Mobile-Phone Translation Services for World Travelers. In: COLING 2008 22nd International Conference on Computational Linguistics: Demonstration Papers, pp. 165–168. COLING Demos (2008)Google Scholar
  4. 4.
    Hazel, M., Mervyn, A.J.: Scenario-Based Spoken Interaction with Virtual Agents. In: Computer Assisted Language Learning, vol. 18, pp. 171–191. Routledge, part of the Taylor & Francis Group (2005)Google Scholar
  5. 5.
    Rangarajan, V., Bangalore, S., Jimenez, A., Golipour, L., Kolan, P.: SPECTRA: A Speech-to-Speech Translation System in the Cloud. In: IEEE International Conference on Emerging Signal Processing Applications (2013)Google Scholar
  6. 6.
    Mozer, T.: Speech’s Evolving Role in Consumer Electronics …From Toys to Mobile. In: Neustein, A., Markowitz, J.A. (eds.) Mobile Speech and Advanced Natural Language Solutions, pp. 23–34. Springer (2013)Google Scholar
  7. 7.
    Delmonte, R.: Getting Past the Language Gap: Innovations in Machine Translation. In: Neustein, A., Markowitz, J.A. (eds.) Mobile Speech and Advanced Natural Language Solutions, pp. 103–181. Springer (2013)Google Scholar
  8. 8.
    Marietto, M.D.G.B., Varago, R.A., Oliveira, G.B., Botelho, W.T., Pimentel, E., Robson, S.F., Silva, V.L.: Artificial Intelligence Markup Language: A Brief Tutorial. International Journal of Computer Science & Engineering Survey 4(3) (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Inese Vīra
    • 1
  • Jānis Teseļskis
    • 1
  • Inguna Skadiņa
    • 1
  1. 1.TildeRigaLatvia

Personalised recommendations