Baylor University
Waco, Texas, 76798, United States
NCT Number: NCT05599165
The protocol has two aims; Aim 1 involves two experiments and Aim 2 involves three experiments. Under Aim 1, the investigator will identify that the frequency and time ranges of consonants produce consonant enhancement (i.e., "target frequency range" and "target time range", respectively), and that the frequency and time ranges of consonants cause consonant confusions (i.e., "conflicting frequency range" and "conflicting time range", respectively). Aim 2 tests the effects of the frequency and time ranges, identified through Aim 1 on consonant recognition with each of the four signal processing conditions: no signal processing (i.e., control condition), the target frequency and time ranges intensified alone, the conflicting frequency and time ranges suppressed alone, and both target range intensification and conflicting range suppression.
Looking for future studies?
Notify Me18 year–74 year
All sexes
Interventional
Not applicable
Waco, Texas, 76798, United States
Speech perception for those who use cochlear implants (CIs) in combination with hearing aids (HAs) in opposite ears (i.e., bimodal hearing) varies greatly. This variability depends on the users' ability to process frequency and time information critical for speech perception. By identifying and enhancing this acoustic information, speech perception will significantly improve. In this AREA project, the investigators aim to establish and verify a tailored identification scheme for the spectral and temporal cues responsible for consonant recognition. The recent bimodal study conducted in the investigator's research laboratory shows that some frequency ranges and time segments of consonants are critical for consonant enhancement (called "target frequency or time ranges") while other frequency and time ranges cause consonant confusions (called "conflicting frequency or time ranges"). An Articulation Index-Gram (AI-Gram) signal processing can add and suppress intensity on these target and conflicting ranges. In Aim 1, the investigators will determine the effect of the dead regions on consonant recognition. Target and conflicting ranges will then be identified on an individual subject basis for each consonant in the HA alone, CI alone, and CI+HA in quiet. The target frequency range will be determined by finding the frequency regions creating dramatic consonant enhancement, while the conflicting frequency ranges will be determined by finding the frequency regions creating consonant confusion. The target time ranges will be determined by finding the segment of the consonants responsible for dramatic consonant improvement while systematically truncating the consonant. The target time range will be used as the conflicting time ranges because the conflicting frequency ranges would be the most detrimental factor affecting the target frequency ranges if they coincide in time. In Aim 2, consonant recognition will be measured in quiet and noise under the three AI-Gram processing conditions: 1) target ranges alone with +6 dB gain; 2) conflicting ranges alone with -6 dB suppression; and 3) both intensified target and suppressed conflicting ranges. For each AI-Gram processing condition, consonant recognition will be measured in the matched listening conditions (e.g., the target or conflicting ranges identified in the HA alone will be presented in the HA alone listening condition). To determine how the unilateral detection ability affects bimodal benefit, the consonants processed on the target or conflicting ranges identified in the HA alone and CI alone will each be presented to the CI+HA listening condition. This proposed work will identify acoustic cues that contribute to bimodal benefit and will reveal how these cues are integrated or interfered with across modalities. Defining the relative impact of the target and conflicting ranges on the AI-Gram-sensitive consonants in the HA alone, the CI alone, and the CI+HA together will help determine the upper and lower cutoff frequencies of a HA and a CI and fine-tune these cutoff frequencies. This data is much needed for the long-term goal: developing a tailored bimodal fitting procedure.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
The proposed work requires the following qualifications to be met:
Consonant recognition will be measured in noise without any signal processing.
Time frame: 24 weeks
Percent correct scores, ranging from minimum 0% to maximum 100% in consonant perception scores will be compared under three signal processing conditions: (1) when no signal processing is applied to consonants (baseline), (2) when the target frequency and time ranges responsible for consonant perception are intensified, and (3) when the conflicting frequency and time ranges causing consonant confusions are removed. Higher percent correct scores mean a better outcome.
Baylor University
Other
Speech Perception Enhancement Using Novel Signal Processing in Bimodal Hearing
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
Published trials that share one or more normalized conditions with this study.
NCT06424262
Ear Diseases, Hearing Disorders
Sydney, New South Wales, Australia
View Trial DetailsNCT03686046
Ear Diseases, Hearing Disorders
San Diego, California, United States
View Trial DetailsNCT07667140
Ear Diseases, Hearing Disorders
Oldenburg, Germany
View Trial DetailsNCT06176625
Behavior, Behavioral Symptoms
Baltimore, Maryland, United States
View Trial Details