Gisting conversational speech

Author

Rohlicek, J.R. ; Ayuso, D. ; Bates, M. ; Bobrow, R. ; Boulanger, A. ; Gish, H. ; Jeanrenaud, P. ; Meteer, M. ; Siu, M.

Author_Institution

BBN Systems & Technologies, Cambridge, MA, USA

Volume

2

fYear

1992

Firstpage

113

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

air-traffic control; aircraft communication; speech recognition; Dallas-Fort Worth airport; air traffic control communications; algorithms; flight identifications; landing; natural language parsing; signal segmentation; speaker segregation; speech recognition; stereotyped voice traffic; takeoff; topic classification; tower recording; Airports; Clustering algorithms; Data mining; Databases; Event detection; Fasteners; Monitoring; Poles and towers; Speech enhancement; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on

ISSN

1520-6149

Print_ISBN

0-7803-0532-9

Type

conf

DOI

10.1109/ICASSP.1992.226107

Filename

226107