ISSN : 1796-2048
Volume : 2    Issue : 5    Date : September 2007

Single-Ended Quality Measurement of Noise Suppressed Speech Based on Kullback-Leibler Distances
Tiago H. Falk, Hua Yuan and Wai-Yip Chan
Page(s): 19-26
Full Text:
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In this paper, a single-ended quality measurement algorithm for noise suppressed speech is
described.The proposed algorithm computes fast approximations of Kullback-Leibler distances between
Gaussian mixture (GM) reference models of clean, noise corrupted, and noise suppressed speech and a
GM model trained online on the test speech signal. The distances, together with a spectral flatness
measure, are mapped to an estimated quality score via a support vector regressor. Experimental results
show that substantial improvement in performance and complexity can be attained, relative to the current
state-of-art single-ended ITU-T P.563 algorithm. Due to its modular architecture, the proposed algorithm
can be easily configured to also perform signal distortion and background intrusiveness measurement, a
functionality not available with current standard algorithms.

Index Terms
Single-ended measurement, speech quality, Gaussian mixture model, Kullback-Leibler distance, noise