Improved Voice Activity Detection Based on Iterative Spectral Subtraction and Double Thresholds for CVR

Abstract

Cockpit voice recorder (CVR) in aircraft black box records many cockpit voices, such as speaker voices, noises and background sounds with special meanings. Cockpit voices' complexity exacerbates analysis difficulty through traditional differentiating and hearing methods, so that fresh cockpit voices are not captured easily from non-stationary sounds. In this paper, by analyzing firstly thoroughly characteristics of cockpit voices, we develop an improved voice activity detection scheme based on iterative spectral subtraction and double thresholds. Finally, to demonstrate the effectiveness of the proposed scheme, we make simulations with a section of speech (SNR=8) from standard voice bank and a section of true cockpit voice and compare the probabilities and of three algorithms, where denotes probability of correctly detecting speech frames probability of correctly detecting noise frames. Simulation results are presented to demonstrate the effectiveness of the improved algorithm.