Evaluation of the sparse coding shrinkage noise reduction algorithm in normal hearing and hearing impaired listeners.

Evaluation of the sparse coding shrinkage noise reduction algorithm in normal hearing and hearing impaired listeners. Hear Res. 2014 Feb 1; Authors: Sang J, Hu H, Zheng C, Li G, Lutman ME, Bleeck S Abstract Although there are numerous single-channel noise reduction strategies to improve speech perception in noise, most of them improve speech quality but do not improve speech intelligibility, in circumstances where the noise and speech have similar frequency spectra. Current exceptions that may improve speech intelligibility are those that require a priori knowledge of the speech or noise statistics, which limits practical application. Hearing impaired (HI) listeners suffer more in speech intelligibility than normal hearing listeners (NH) in the same noisy environment, so developing better single-channel noise reduction algorithms for HI listeners is justified. Our model-based "sparse coding shrinkage" (SCS) algorithm extracts key speech information in noisy speech. We evaluate it by comparison with a state-of-the-art Wiener filtering approach using speech intelligibility tests with NH and HI listeners. The model-based SCS algorithm relies only on statistical signal information without prior information. Results show that the SCS algorithm improves speech intelligibility in stationary noise and is comparable to the Wiener filtering algorithm. Both algorithms improve intelligibility for HI listeners but not for NH listeners. Improvement is less ...
Source: Hearing Research - Category: Audiology Authors: Tags: Hear Res Source Type: research