Extending the articulation index to account for non-linear distortions introduced by noise-suppression algorithms

The conventional articulation index (AI) measure cannot be applied in situations where non-linear operations are involved and additive noise is present. This is because the definitions of the target and masker signals become vague following non-linear processing, as both the target and masker signals are affected. The aim of the present work is to modify the basic form of the AI measure to account for non-linear processing. This was done using a new definition of the output or effective SNR obtained following non-linear processing. The proposed output SNR definition for a specific band was designed to handle cases where the non-linear processing affects predominantly the target signal rather than the masker signal. The proposed measure also takes into consideration the fact that the input SNR in a specific band cannot be improved following any form of non-linear processing. Overall, the proposed measure quantifies the proportion of input band SNR preserved or transmitted in each band after non-linear processing. High correlation (r?=?0.9) was obtained with the proposed measure when evaluated with intelligibility scores obtained by normal-hearing listeners in 72 noisy conditions involving noise-suppressed speech corrupted in four different real-world maskers.