Effect of temporal fine structure on speech intelligibility modeling

Temporal fine structure (TFS) carries important information for the speech perception of hearing-impaired listeners and for the design of novel prosthetic hearing devices. This study assessed the performance of present intelligibility indices for predicting the intelligibility of speech containing different amount of TFS information. Speech intelligibility data was collected from vocoded and wideband Mandarin sentences containing little/partial and intact TFS information, respectively, and was then subjected to the correlation analysis with existing intelligibility indices. It was found that, though performing well in predicting the intelligibility of vocoded or wideband speech separately, present intelligibility indices were not highly correlated with the intelligibility scores when a general function was used to map all intelligibility measures to intelligibility scores. Analysis further showed that the intelligibility prediction power could be significantly improved when multiple condition-dependent functions were used for mapping intelligibility measures to intelligibility scores.

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