Evaluation of a near-end listening enhancement algorithm by combined speech intelligibility and listening effort measurements

J Acoust Soc Am. 2018 Oct;144(4):EL315. doi: 10.1121/1.5064956.

Abstract

Previous studies showed that near-end listening enhancement (NELE) algorithms can significantly improve speech intelligibility in noisy environments. This study investigates the benefit of the NELE algorithm AdaptDRC in normal-hearing listeners at signal-to-noise ratios (SNRs) for which speech intelligibility is at ceiling, by evaluating listening effort for processed and unprocessed speech in the presence of speech-shaped and cafeteria noise. The results suggest that the NELE algorithm is able to reduce listening effort over a wide range of SNRs. Hence, listening effort seems to be applicable for evaluating NELE algorithms over a much wider SNR range than speech intelligibility.

Publication types

  • Research Support, Non-U.S. Gov't