Supporting Equity and Inclusion of Deaf and Hard-of-Hearing Individuals in Professional Organizations.

Disability is an important and often overlooked component of diversity. Individuals with disabilities bring a rare perspective to science, technology, engineering, mathematics, and medicine (STEMM) because of their unique experiences approaching complex issues related to health and disability, navigating the healthcare system, creatively solving problems unfamiliar to many individuals without disabilities, managing time and resources that are limited by physical or mental constraints, and advocating for themselves and others in the disabled community. Yet, individuals with disabilities are underrepresented in STEMM.

Prediction of Individual Cochlear Implant Recipient Speech Perception With the Output Signal to Noise Ratio Metric.

Objectives: A cochlear implant (CI) implements a variety of sound processing algorithms that seek to improve speech intelligibility. Typically, only a small number of parameter combinations are evaluated with recipients but the optimal configuration may differ for individuals. The present study evaluates a novel methodology which uses the output signal to noise ratio (OSNR) to predict complete psychometric functions that relate speech recognition to signal to noise ratio for individual CI recipients.

An Investigation of Audibility Effects on Cochlear Implant Speech Perception Prediction.

Output Signal to Noise Ratio (OSNR) is the Signal to Noise Ratio (SNR) at the output of a cochlear implant (CI) sound processor. Whereas other prediction metrics typically predict mean speech-in-noise test scores for a group of subjects, an OSNR-based model has been shown to accurately predict scores for individual CI recipients. The OSNR model was unable to predict scores for aggressive Ideal Binary Mask (IdBM) sound processing.

An Investigation of the Effect of AGC Gain on the Output Signal to Noise Ratio in Cochlear Implant Sound Processing.

Measurement of speech intelligibility of cochlear implant (CI) recipients is typically carried out with a speech-innoise test procedure. Metrics which predict speech intelligibility can pre-screen new sound processing strategies prior to comprehensive testing with human subjects.The Output Signal to Noise Ratio (OSNR) metric calculates the Signal to Noise Ratio (SNR) which is present at the CI sound processor output.

An Evaluation of Output Signal to Noise Ratio as a Predictor of Cochlear Implant Speech Intelligibility.

Objectives: Cochlear implant (CI) sound processing strategies are usually evaluated in clinical studies involving experienced implant recipients. Metrics which estimate the capacity to perceive speech for a given set of audio and processing conditions provide an alternative means to assess the effectiveness of processing strategies. The aim of this research was to assess the ability of the output signal to noise ratio (OSNR) to accurately predict speech perception.

A simulation analysis of the variability of the roving level hearing test.

In the study of auditory prostheses, the Speech Recognition Threshold (SRT) is the Signal to Noise Ratio (SNR) at which 50% of words are correctly identified. SRT is typically measured using an adaptive procedure wherein speech is presented at a fixed sound pressure level (SPL) and the noise level is varied according to the subject's responses. A roving level SRT test has been used by researchers with the goal of including the effectiveness of Automatic Gain Control (AGC) systems in SRT measurements.