A multi-mode network typically consists of multiple heterogeneous social actors among which various types of interactions could occur. Identifying communities in a multi-mode network can help understand the structural properties of the network, address the data shortage and unbalanced problems, and assist tasks like targeted marketing and finding… (More)
This paper describes a domain-independent, machine-learning based approach to temporally anchoring and ordering events in news. The approach achieves 84.6% accuracy in temporally anchoring events and 75.4% accuracy in partially ordering them.
In this paper, we developed a highly efficient frame-level on-line adaptive voice activity detection (VAD) algorithm for the telephone-based CU Communicator spoken dialog system. The adaptive algorithm uses prior speaker and channel statistics as well as acoustic features of current sample frames to update model parameters. The algorithm achieved .05xRT in… (More)
A new sensitive microwave life-detection system which can be used to locate human subjects buried under earthquake rubble or hidden behind various barriers has been constructed. This system operating at 1150 MHz or 450 MHz can detect the breathing and heartbeat signals of human subjects through an earthquake rubble or a construction barrier of about 10-ft… (More)
This paper presents some up-to-date audio processing techniques which have been developed and integrated into the University of Colorado (CU) communicator system. The CU Communicator is an interactive human-machine dialogue system for airline, hotel and rental car information. The baseline system was fully functional in June 1999. Since then, many… (More)
This paper presents a simple and effective rule learning algorithm for highly unbalanced data sets. By using the small size of the minority class to its advantage this algorithm can conduct an almost exhaustive search for patterns within the known fraudulent cases. This algorithm was designed for and successfully applied to a law enforcement problem, which… (More)