We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the
NIH Research Portfolio Online Reporting Tools and the
NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
You can help! If you notice any innacuracies, please
sign in and mark grants as correct or incorrect matches.
Sign in to see low-probability grants and correct any errors in linkage between grants and researchers.
High-probability grants
According to our matching algorithm, Sean Adam Davidson is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2006 — 2007 |
Davidson, Sean A |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
Cues For Detection of Tones in Reproducible Noises
[unreadable] DESCRIPTION (provided by applicant): This proposal describes a psychophysical experiment and modeling techniques designed to identify cues used by human listeners for detection of sounds in noisy environments. Understanding potential detection cues will help to develop effective signal-processing strategies for hearing aids, cochlear implants, noise-reduction systems, etc., by preserving cues that are vital for detection of sounds of interest. Here a psychophysical tone-in-noise detection experiment is proposed that utilizes prerecorded noise waveforms. The waveforms will be manipulated such that the contributions of temporal fine-structure and temporal envelope-based cues can be quantified while overall stimulus energy is held constant. Detection performance for individual masking waveforms will be characterized under several diotic and binaural conditions. The prerecorded noises will also be used to test critical modeling assumptions under a variety of stimulus configurations and bandwidths. Modeling efforts will incorporate results from the proposed (and other) experiments in order to predict multiple listeners' abilities and strategies, including identification of potential cues for extracting signals from noise waveforms. [unreadable] [unreadable] [unreadable]
|
0.936 |