Gisting conversational speech in real time

The authors describe additions and modifications to a prototype system for analyzing air traffic contol (ATC) communication. The primary goal of the effort was to achieve real-time performance. This involved both system architectural and algorithmic modifications. The task of the system is to extract the gist of activity as it is monitored. In the ATC domain this involves identifying those flights that are present and classifying each flight as a departure, arrival, or other. The system combines a variety of techniques from speaker-identification, speech recognition, natural-language processing, and artificial intelligence. Continuous processing versions of the algorithms have been constructed and it has been demonstrated that real-time performance is possible by distributing the processing over a small number of workstations. To accomplish this task, a flexible software task-construction tool that allows simple specification of complex systems, supporting both dataflow and client/server models, has been developed.<>