Enhancement of electrolarynx speech based on auditory masking

Abstract

Electrolarynx (EL) speech provides a valuable means of verbal communication for the laryngectomees. Yet EL speech tends to be less intelligible speech due to the presence of background noise. This paper addresses the issue of EL speech enhancement. The proposed approach takes into account the frequency-domain masking properties of the human auditory system for a subtractive-type enhancement process. Subtractive-type algorithms can efficiently reduce the radiated noise of EL speech but not to reduce the additive noise from the environment due to the use of fixed subtraction parameters. Considering the particular characteristics of EL speech, a new computationally efficient algorithm based on the perceptual weighting technique is developed to adapt the subtraction parameters. This leads to a significant reduction of the unnatural structure of the residual noise. Acoustic and perceptual experiments confirm that the enhanced EL speech is more pleasant to human listeners and the proposed algorithm results in improved performance over classical subtractive-type algorithms.