Cochlear Implant Speech and Non-speech Sound Recognition

Overview

The primary purpose of the research is to study how synthesized speech and non-speech percepts (sounds) are recognized in subjects with cochlear implants (CI) who are not getting functional speech recognition using existing speech to CI algorithms. By identifying a partial set of phonemes (units of speech) from this CI feedback, a new language could be developed.

A cochlear implant (CI) is a small, complex electronic device used by the profoundly deaf or severely hard-of-hearing. The CI has two main components: 1. The externally worn microphone, sound processor and transmitter system; 2. The implanted receiver and electrode system sending electrical currents to the inner ear; whereby the external and internal components are held together by a magnet. The CI does not restore normal hearing; however, it does provide a small representation of sounds in the environment and help him or her to understand speech. Due to the limited capacity of the CI, hearing is vastly different from normal hearing and it is difficult to really understand what they are hearing; hence, the varying outcomes of CI users. Most of the current research on cochlear implants (CI) aims to improve speech recognition for spoken English. However, patients who have a cochlear implant late in life-basically after childhood-have a very limited ability to learn speech. Late implant CI recipients do not distinguish speech sounds well, but it is not known if non-speech sounds can be differentiated, and if so, whether they can be used to create a functional language. Honeder et al studied the latest CI to determine the impact of a new audio processor on speech perception in noise. Overall, this new CI may improve hearing performance especially in difficult listening situations; however, due to inconsistencies in technical setups, speech processors, coding strategies, spatial conditions, spectral and temporal noise characteristics, speech testing paradigms, and subjects' ear they were unable to find significant improvements. Thus, demonstrating the challenge of understanding truly, what CI users hear and understand. Usher Syndrome is the most common inherited condition where children are born with moderate to profound hearing loss, depending on the type affecting. Usher syndrome affects approximately 4 to 17 per 100,000 people, and accounts for about 50 percent of all hereditary deaf-blindness cases. Usher's syndrome affects three to six percent of all children who are deaf and who are hard-of-hearing. Of the three types, types 1 and 2 are the most common and make up about 95% of the reported cases. Since genetic factors are the most commonly known etiology for Usher's Syndrome, it is very difficult to know what exactly the effected patient might hear or understand while using a CI. A systematic review by Nishio et al showed relatively good CI outcomes; however, there have only been limited studies conducted on patients with other gene mutations. Overall, CI patients report improvements in speech and quality of life. Unfortunately, the exact mechanisms of how and what Usher Syndrome CI users' process still requires further investigation. Despite the historical usage and various advancements in computer technology for CIs, the hearing world has yet to implement underutilized methodology and technology to further train, assess, and advance the capabilities of CIs. More importantly, simulation hearing labs providing a standardized, patient controlled environment with high-fidelity tracking and monitoring hearing simulations using a keyboard synthesizer (Cognate) attached to an external CI will allow for a more comprehensive evaluation of the CI users' hearing experience, assimilation, interpretation, and user controlled actions. Cognate is a simplified and more structured speech synthesizer. The synthesizer will generate the CI output, an acoustic output, and a visual display of the acoustic signals and CI output on the monitor and record the outputs of the synthesizer. Cognate would be an alternate 'English' encoding CI system that might be simpler to learn, and would translate written English, not spoken English. Cognate would translate text into percepts (sounds) that the subject would 'hear'. These percepts (sounds) would be equivalent in a sense to phonemes (letters). With a partial set of phonemes (English uses 45 for very computer sounding speech synthesis), a new language could be developed. The feasibility and data from this study will be used for future studies to evolve the Cognate encoding CI system, especially for Usher Syndrome patients.

Conditions

Interventions

Eligibility

Locations (1)

Outcomes