Enhancing Air Traffic Management Security by Means of Conformance Monitoring and Speech Analysis

This document describes the concept of an air traffic management security system and current validation activities. This system uses speech analysis techniques to verify the speaker authorization and to measure the stress level within the air-ground voice communication between pilots and air traffic controllers on one hand, and on the other hand it monitors the current air traffic situation. The purpose of this system is to close an existing security gap by using this multi-modal approach. First validation results are discussed at the end of this article.

[1]  John H. L. Hansen,et al.  Effects of phoneme characteristics on TEO feature-based automatic stress detection in speech , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[2]  J. Russell.  A circumplex model of affect. , 1980 .

[3]  John H. L. Hansen,et al.  Speech Under Stress: Analysis, Modeling and Recognition , 2007, Speaker Classification.

[4]  Mykola Pechenizkiy,et al.  Stress detection from speech and Galvanic Skin Response signals , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[5]  Milan Rusko,et al.  Stress, Arousal, and Stress Detector Trained on Acted Speech Database , 2016, SPECOM.

[6]  Klaus R. Scherer,et al.  Vocal communication of emotion: A review of research paradigms , 2003, Speech Commun..

[7]  Michael Finke,et al.  Using speech analysis in voice communication: A new approach to improve air traffic management security , 2016, 2016 7th IEEE International Conference on Cognitive Infocommunications (CogInfoCom).

[8]  Aladdin M. Ariyaeeinia,et al.  Relative effectiveness of score normalisation methods in open-set speaker identification , 2004, Odyssey.

[9]  Peter Baranyi,et al.  Cognitive infocommunications: CogInfoCom , 2010, 2010 11th International Symposium on Computational Intelligence and Informatics (CINTI).

[10]  Alvin F. Martin,et al.  The DET curve in assessment of detection task performance , 1997, EUROSPEECH.

[11]  John H. L. Hansen,et al.  Classification of speech under stress using target driven features , 1996, Speech Commun..

[12]  Douglas A. Reynolds,et al.  Robust text-independent speaker identification using Gaussian mixture speaker models , 1995, IEEE Trans. Speech Audio Process..

[13]  Patrick Kenny,et al.  Front-End Factor Analysis for Speaker Verification , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[14]  Douglas A. Reynolds,et al.  Analysis of multitarget detection for speaker and language recognition , 2004, Odyssey.

[15]  Jozef Juhar,et al.  A Study of Acoustic Features for Emotional Speaker Recognition in I-Vector Representation , 2015 .