Segmentation and classification of meetings using multiple information streams

ABSTRACT

We present a meeting recorder infrastructure used to record and annotate events that occur in meetings. Multiple data streams are recorded and analyzed in order to infer a higher-level state of the group's activities. We describe the hardware and software systems used to capture people's activities as well as the methods used to characterize them.

REFERENCES

• 1: S. Banerjee, J. Cohen, T. Quisel, A. Chan, Y. Patodia, Z. Al-Bawab, R. Zhang, A. Black, R. Stern, R. Rosenfeld, A. Rudnicky, P. E. Rybski, and M. Veloso. Creating multi-modal, user-centric records of meetings with the carnegie mellon meeting recorder architecture. In Proceedings of the ICASSP 2004 Meeting Recognition Workshop, Montreal, Canada, May 2004.
• 2: S. Banerjee and A. I. Rudnicky. Using simple speech--based features to detect the state of a meeting and the roles of the meeting participants. In Proceedings of the 8th International Conference on Spoken Language Processing (Interspeech 2004 -- ICSLP), Jeju Island, Korea, 2004.
• 3: L. R. Rabiner. A tutorial on Hidden Markov Models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257--286, 1989.
• 4: P. E. Rybski, F. de la Torre, R. Patil, C. Vallespi, M. M. Veloso, and B. Browning. Cameo: The camera assisted meeting event observer. In International Conference on Robotics and Automation, New Orleans, April 2004.
• 5: H. Schneiderman. Feature-centric evaluation for cascaded object detection. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2004.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.m Miscellaneous

General Terms:
Human Factors

Keywords:
meeting understanding, multi-modal interfaces