Conversational Informatics (E) (2017)

10:30-12:00 on Wednesday, Second Semester
Lecture Room #3, Research Building #7

This course is jointly taught by Prof. Toyoaki Nishida and Prof. Yoshimasa Ohmoto.

Overview

Conversational interaction is considered to be a powerful communication means for intelligent actors, either natural or artificial, to interact each other to act as a collective intelligence.  In this course, we study the mechanism of conversational interactions with verbal and nonverbal cues from computational points of view and discuss key issues in designing conversational systems that can interact with people in a conversational fashion.

Agenda (planned)

  1. Introduction (October 4)  Nishida
    Slides
  2. Cognitive Interaction Design (October 11) Ohmoto
    slide
  3. History of Conversational Systems (October 18) Nishida
    Slides
  4. Methodologies for Conversational System Development (October 25) Nishida
  5. Affective Computing (November 1) Nishida
  6. Theory of Mind (November 8) Nishida
  7. Smart Conversation Space (November 15) Ohmoto
  8. Measurement, Analysis and Modeling (November 22) Ohmoto
  9. Learning by Imitation – 1 (November 29) Nishida
  10. Learning by Imitation – 2 (December 6) Nishida
  11. Aspects of Conversation – 1 (December 13) Nishida
  12. Aspects of Conversation – 2 (December 20) Nishida
  13. Aspects of Conversation – 2 (December 27)  Nishida
  14. Synergy and Wrap up (January 10) Nishida

Course materials

  1. Textbook :
    Toyoaki Nishida, Atsushi Nakazawa, Yoshimasa Ohmoto, Yasser Mohammad. Conversational Informatics―Data Intensive Approach with Emphasis on Nonverbal Communication, Springer 2014.
    http://link.springer.com/book/10.1007%2F978-4-431-55040-2
  2. Reading:
    Yasser Mohammad and Toyoaki  Nishida. Data Mining for Social Robotics – Toward Autonomously Social Robots, Springer 2015.
    http://www.springer.com/us/book/9783319252308
  3. Additional materials will be provided by lecturers.

Credits

Will be awarded based on a report on subjects given at the class.  Due date (January 31st, 2017)

Take-Home Knowledge

  1. Students will develop fundamental knowledge, including the history of the field and potential applications, for learning more advanced subjects on human-agent interaction.
  2. Students will obtain minimal skill for conducting experiment to take an empirical approach to human-agent interaction.