Evaluation of a near-end listening enhancement algorithm by combined speech intelligibility and listening effort measurements
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Published on: October 11, 2010
J Rennies1, A Pusch2, H Schepker3
1Department of Speech, Language and Hearing Sciences and Hearing Research Center, Boston University, Boston, Massachusetts 02215, USA.
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.
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