A frequent complaint of hearing aid users is that amplification does not improve speech reception in noisy listening situations. Manufacturers of hearing aids have begun to address this problem by introducing instruments that aim to minimize noise interference by modifying the frequency-gain characteristic as a function of input speech-plus-noise spectrum. While recent research indicates that of this type of noise-reduction approach can be beneficial, the effectiveness of specific control algorithms is not known because no quantitative frame of reference for considering the problem or evaluating proposed solutions has been developed.
This research aims to (1) find frequency-gain characteristics that will optimize speech intelligibility for specific well-defined noisy listening conditions; (2) test the Articulation Index (AI) model's solution, which calls for preserving the audibility of portions of the speech spectrum not masked by noise and reducing spread of masking effects; and (3) assess and improve the AI model and other resulting strategies for hearing aid applications, using data from a large clinical population. In the laboratory, speech in a variety of noise backgrounds processed by AI- prescribed characteristics and several alternate solutions will be presented to hearing.impaired subjects for comparison on the basis of speech recognition test scores, residual speech spectrum audibility (AI), side-by-side listening comparisons, and ratings on several dimensions of sound acceptability and quality. In the audiology clinic, representative condition(s) will be selected and incorporated into the audiologic test routine in an effort to verify laboratory findings. Results of the proposed experiments will form a basis for devising algorithms that maximize speech reception in noise as well as selecting adaptive frequency response hearing aids and adjusting them on an individual subject basis.
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