The objective intelligibility assessment of nonlinearly enhanced speech is a widely experienced problem. Nonlinear processors operate primarily on the low-level and transient components of speech. As these sections contain important acoustic cues as well as context-constitutive information, they dominate speech intelligibility. For that reason, short-time intelligibility measures at low-level and transient components are weighted with their contribution to the overall intelligibility. In this report, spectral features are calculated from auditory sub-bands and are utilized to label these sections of high information content. A genetic optimization is performed to adapt the spectral feature measures to psychoacoustical data. No improvement is found over existing methods of objective speech intelligibility assessment, using short-time intelligibility calculation and level-dependent weighting. Therewith, the reported results contribute to pinpoint practicable solutions to the problem.
Bibliographic reference. Schlesinger, Anton / Boone, Marinus M. (2010): "The characterization of the relative information content by spectral features for the objective intelligibility assessment of nonlinearly processed speech", In INTERSPEECH-2010, 1309-1312.