SNR loss: A new objective measure for predicting the intelligibility of noise-suppressed speech

Most of the existing intelligibility measures do not account for the distortions present in processed speech, such as those introduced by speech-enhancement algorithms. In the present study, we propose three new objective measures that can be used for prediction of intelligibility of processed (e.g., via an enhancement algorithm) speech in noisy conditions. All three measures use a critical-band spectral representation of the clean and noise-suppressed signals and are based on the measurement of the SNR loss incurred in each critical band after the corrupted signal goes through a speech enhancement algorithm. The proposed measures are flexible in that they can provide different weights to the two types of spectral distortions introduced by enhancement algorithms, namely spectral attenuation and spectral amplification distortions. The proposed measures were evaluated with intelligibility scores obtained by normal-hearing listeners in 72 noisy conditions involving noise-suppressed sp...

• Type: Journal
• Year: 2011
• Where: SPEECH
• Authors: Jianfen Ma, Philipos C. Loizou
• Keywords: Algorithms, Enhancement Algorithms, Noisy Conditions, Security Privacy, SPEECH 2011