Multi-Measure Speech Perception in Noise (MMSPIN) Chart: More Scores, Fewer Tests
Seehear, Llc, Arlington VA
Investigators
Abstract
Project summary. This Phase I will establish the feasibility of increasing audiological diagnostic information by carrying out word- and phoneme-level analyses of open set responses during speech audiometry and by obtaining subjective hearing measures. Speech audiometry is used in characterizing functional hearing in settings of hearing screening, diagnosis, hearing aid fitting, counseling, aural rehabilitation/training, occupational fitness, and research. A typical procedure used with word and sentence tests in background noise is to ask the client/patient to repeat back what was just said (i.e., give an open set response). Responses are then scored in terms of words or keywords correct/incorrect. This method discards potentially diagnostic information in response errors, because noise can reveal systematic phonetic feature or phoneme confusions, and with background babble, intrusions from the babble. Other response patterns attributable to cognitive or memory declines may manifest in the paucity or verbosity of response words. Specific types of phoneme perception errors are thought to be associated with extent and configuration of hearing loss; and different types of noise maskers (i.e., energetic and informational maskers) present different types of perceptual problems that vary in severity across individuals. In order to utilize response errors, computational methods are needed to establish their relationships to the stimulus. This is because response errors may incorporate incorrect stimulus-to-response phoneme substitutions, as well as insertions or deletions of phonemes or words relative to the stimulus. We have developed sequence alignment methods to mine errors during speech audiometry, which we propose to evaluate using our system (Multi-Measure SPIN Chart: MMSPIN Chart). MMSPIN chart will be further developed and installed in the George Washington University Speech & Hearing Center (Aim 1). Audiologists will use the system during QuickSin sentence and NU-6 word testing with 200 clients (18-85 years of age) who give permission to access their entire clinic records (Aim 2). Their conventional speech audiometry will be augmented by obtaining subjective hearing accuracy judgments and hearing self-efficacy measures. These subjective judgments are designed to expose discrepancies with objective performance and to reveal individual differences in social cognition associated with hearing loss, both of which may account for the large individual differences in performance and intervention outcomes not accounted for by the audiogram. Evaluation of results in Aim 3 will include developing group and individual profile models comprising objective and subjective clinical data. With our clinician partners, we will develop formats for communicating MMSPIN Chart results to clients. In Aim 4, we will present results in a public lecture for audiologists and solicit opinions about how our new results may best impact clinical practice. Our approach can deliver more informative and efficient speech audiometry using existing test materials and can pave the way to more sensitive speech audiometry, including tests that are adaptive to specific levels of speech processing difficulty.
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