<p> Nonlinear amplification schemes for hearing aids have been developed to deal primarily with the problem of loudness recruitment. The most commonly used form of nonlinear amplification is wide-dynamic-range compression (WDRC). Unfortunately, finding WDRC characteristics that satisfactorily deal with loudness recruitment while maintaining good speech intelligibility has proven difficult. An alternative nonlinear scheme, Advanced Dynamic Range Optimization (ADRO), has been shown in several studies to provide better speech intelligibility and listening comfort than fast-acting WDRC. ADRO uses a set of fuzzy-logic rules to make gain changes to optimize audibility, comfort, protection against loud sound, and noise attenuation. The "hearing protection" gain rule acts instantaneously, whereas the audibility and comfort rules adjust the gain slowly, such that ADRO provides linear amplification most of the time.</p> <p> The goal of this study is to examine the physiological basis for the relative performance of linear amplification, WDRC, and ADRO. Sentences from the TIMIT Speech Database were processed by each algorithm. In the case of WDRC, both single-channel and multi-channel schemes with fast and slow dynamics were tested. Speech signals were presented at 52, 62, 74, and 82 dB SPL (sound pressure level) with various noise levels and types, to simulate real-life environments. The simulations first use an auditory-periphery model to generate a "neurogram" of the auditory nerve's representation of the test speech material. The spectral and temporal modulations in the
neurogram are then analyzed by a model of cortical speech processing. The effects of the
background noise, the presentation level, the hearing loss and the amplification scheme are evaluated by comparing the cortical model response for a given condition (the "test" response) to the cortical model response to the same TIMIT sentence presented in quiet at
65 dB SPL to the normal-hearing model (the "template" response). From the difference
between the test and template responses, a spectro-temporal modulation index (STMI) value is calculated. High STMI values predict good speech intelligibility, while low values predict poor intelligibility. Results show that ADRO is better at restoring the neural representation of speech than the other algorithms tested, even when the WDRC algorithms utilize slow time constants. In the case of no background noise, all the algorithms perform similarly well. However, when background noise is added, STMI values for higher SPLs drop notably for all the algorithms except for ADRO, which sustains a stable value throughout the range of SPLs test.</p> / Thesis / Master of Engineering (MEngr)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/22363 |
| Date | 08 1900 |
| Creators | Leung, Benedict K. H. |
| Contributors | Bruce, Ian C., Electrical Engineering |
| Source Sets | McMaster University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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