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

Jan Rennies | Zendy; Arne Pusch | Zendy; Henning Schepker | Zendy; Simon Doclo | Zendy

Open Access

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

Author(s) -

Jan Rennies,

Arne Pusch,

Henning Schepker,

Simon Doclo

Publication year - 2018

Publication title -

the journal of the acoustical society of america

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.619

H-Index - 187

eISSN - 1520-8524

pISSN - 0001-4966

DOI - 10.1121/1.5064956

Subject(s) - active listening , intelligibility (philosophy) , computer science , speech recognition , psychology , communication , philosophy , epistemology

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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