Field Study Evaluation of Cepstrum Coefficient Speech Analysis for Fatigue in Aviation Cabin Crew

Abstract

Impaired neurobehavioral performance induced by fatigue may compromise safety in 24-hr operational environments such as aviation. As such, non-invasive, reliable, and valid methods of objectively detecting compromised performance capacity in operational settings could be valuable as a means of identifying, preventing, and mitigating fatigue-induced safety risks. One approach that has attracted attention in recent years is quantitative speech analysis, but the extent of its operational feasibility, validity of the metrics, and sensitivity to operationally-relevant factors in aviation remains unknown. To this end, the present report offers an initial proof-of-concept evaluation of a speech analysis method based on Cepstrum Coefficient modeling, using voice files from a broad sample of 195 cabin crew personnel collected during the 2009-2010 U.S. Civil Aerospace Medical Institute-sponsored Flight Attendant Field Study (Roma et al., 2010). Using a personal digital assistant device, participants recited five standardized phrases in random order before and after each workday and sleep episode throughout their respective 3-4 week study periods. Operational acceptability of the procedure was high, as indicated by high protocol compliance and, despite the inherent variability of the timing and environments in which the test sessions occurred, the 13,975 files from 2,795 valid sessions were of sufficient quality for formal analysis. Individualized baseline speech models were built from the files collected during test sessions coinciding with optimal neurobehavioral performance, as determined by 5-min Psychomotor Vigilance Test (PVT) reaction times (RT), then speech deviation scores relative to individual baseline models were calculated for the test sessions that preceded and concluded each trip of multiple consecutive work days. Regarding validity, speech scores correlated significantly with PVT RTs and Lapses (RTs > 500 msec), with a stronger relationship to Lapses,

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2013
Accession Number
ADA601925

Entities

People

  • Andrew M. Mead
  • Harold P. Greeley
  • Melissa M. Mallis
  • Peter G. Roma
  • Steven R. Hursh
  • Thomas E. Nesthus

Organizations

  • Response Applications LLC

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Aerospace Medicine
  • Algorithms
  • Artificial Intelligence
  • Audio Files
  • Commercial Aviation
  • Frequency
  • Health Care
  • Human Factors Engineering
  • Information Science
  • Language
  • Larynx
  • Personal Digital Assistants
  • Reaction Time
  • Regression Analysis
  • Speech Analysis
  • Statistical Analysis
  • Two Dimensional

Readers

  • Aviation Safety Risk Assessment.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Systems Analysis and Design

Technology Areas

  • Space