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

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

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 intel...

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Bibliographic Details
Published in:The Journal of the Acoustical Society of America Vol. 144; no. 4; pp. EL315 - EL321
Main Authors: Rennies, J., Pusch, A., Schepker, H., Doclo, S.
Format: Journal Article
Language:English
Published: 01-10-2018
Online Access:Get full text
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Summary: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.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.5064956