How to talk to a hologram

ABSTRACT

There is a growing need for creating life-like virtual human simulations that can conduct a natural spoken dialog with a human student on a predefined subject. We present an overview of a spoken-dialog system that supports a person interacting with a full-size hologram-like virtual human character in an exhibition kiosk settings. We also give a brief summary of the natural language classification component of the system and describe the experiments we conducted with the system.

REFERENCES

• 1: Jennifer Chu-Carroll , Bob Carpenter, Vector-based natural language call routing, Computational Linguistics, v.25 n.3, p.361-388, Septmeber 1999
• 2: Victor Lavrenko , Martin Choquette , W. Bruce Croft, Cross-lingual relevance models, Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval, August 11-15, 2002, Tampere, Finland [doi>10.1145/564376.564408]
• 3: A. Leuski. Using statistical language models for a dialog response selection. Forthcoming.
• 4: Anton Leuski, Email is a stage: discovering people roles from email archives, Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, July 25-29, 2004, Sheffield, United Kingdom [doi>10.1145/1008992.1009091]
• 5: David D. Lewis , Robert E. Schapire , James P. Callan , Ron Papka, Training algorithms for linear text classifiers, Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval, p.298-306, August 18-22, 1996, Zurich, Switzerland [doi>10.1145/243199.243277]
• 6: B. Pellom. Sonic: The university of colorado continuous speech recognizer. Technical Report TR-CSLR-2001-01, University of Colorado, Boulder, CO, 2001.
• 7: A. Sethy, P. Georgiou, and S. Narayanan. Building topic specific language models from webdata using competitive models. In Proceedings of EUROSPEECH, Lisbon, Portugal, 2005.
• 8: Ioannis Tsochantaridis , Thomas Hofmann , Thorsten Joachims , Yasemin Altun, Support vector machine learning for interdependent and structured output spaces, Proceedings of the twenty-first international conference on Machine learning, p.104, July 04-08, 2004, Banff, Alberta, Canada [doi>10.1145/1015330.1015341]
• 9: E. M. Voorhees. Overview of the trec 2003 question answering track. In Proceedings of The 12th Text Retrieval Conference, pages 54--69, 2003.
• 10: Joseph Weizenbaum, ELIZA—a computer program for the study of natural language communication between man and machine, Communications of the ACM, v.9 n.1, p.36-45, Jan. 1966 [doi>10.1145/365153.365168]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Selection process

Additional Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.m Miscellaneous
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Natural language; Voice I/O

General Terms:
Design, Experimentation, Human Factors

Keywords:
spoken dialog, text classification