Gisting conversational speech
- 1 January 1992
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2 (15206149) , 113-116 vol.2
- https://doi.org/10.1109/icassp.1992.226107
Abstract
A novel system for extracting information from stereotyped voice traffic is described. Off-the-air recordings of commercial air traffic control communications are interpreted in order to identify the flights present and determine the scenario (e.g., takeoff, landing) that they are following. The system combines algorithms from signal segmentation, speaker segregation, speech recognition, natural language parsing, and topic classification into a single system. Initial evaluation of the algorithm on data recorded at Dallas-Fort Worth airport yields performance of 68% detection of flights with 98% precision at an operating point where 76% of the flight identifications are correctly recognized. In tower recording containing both takeoff and landing scenarios, flights are correctly classified as takeoff or landing 94% of the time.Keywords
This publication has 4 references indexed in Scilit:
- Statistical language modeling using a small corpus from an application domainPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Continuous speech recognition results of the BYBLOS system on the DARPA 1000-word resource management databasePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- An unsupervised, sequential learning algorithm for the segmentation of speech waveforms with multiple speakersPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- Segregation of speakers for speech recognition and speaker identificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991