A Comparative Intelligibility Study of Speech Enhancement Algorithms
Yi Hu, Philipos C. Loizou · 2007
In this paper, we report on the evaluation of intelligibility of speech enhancement algorithms. IEEE sentences were corrupted by four types of noise including babble, car, street and train at two SNR levels (0 dB and 5 dB), and then processed by eight speech enhancement methods encompassing four classes of algorithms: spectral subtractive, subspace, statistical model based and Wiener-type algorithms. The processed speech files were presented to normal hearing listeners for identification in formal listening tests. Intelligibility was assessed as the percentage of words identified correctly. This paper reports the results of the intelligibility tests.