Improvements in audio processing and language modeling in the CU communicator

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 improvements have been made. The paper will concentrate on acoustic echo cancellation, voice activity detection (VAD) and language modeling techniques and provide a paradigm for speech and audio processing in a dialog system with barge-in capabilities. Specifically, a real-time block least-mean-square (LMS) algorithm is discussed. A robust voice activity detector using energy threshold is applied to detect user voice. Experimental results are presented and some real-time implementation issues are addressed.