ArticleHearing research2019
Frequency change detection and speech perception in cochlear implant users.
Article in Hearing research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Validation of the acoustic change complex (ACC) prediction model to predict speech perception in noise in adult patients with hearing loss: a study protocol.Diagnostic and prognostic research · 2024Article
- Article
- Relationship Between the Ability to Detect Frequency Changes or Temporal Gaps and Speech Perception Performance in Post-lingual Cochlear Implant Users.Frontiers in neuroscience · 2022Article
- Psychosocial Impact of Assistive Devices and Other Technologies on Deaf and Hard of Hearing People.International journal of environmental research and public health · 2021Article
- The Acoustic Change Complex in Response to Frequency Changes and Its Correlation to Cochlear Implant Speech Outcomes.Frontiers in human neuroscience · 2021Article
- Home-Based Speech Perception Monitoring for Clinical Use With Cochlear Implant Users.Frontiers in neuroscience · 2021Article
- Speech intelligibility and auditory perception of pre-school children with Hearing Aid, cochlear implant and Typical Hearing.Journal of otology · 2020Article
- A Preliminary Study of the Effects of Attentive Music Listening on Cochlear Implant Users' Speech Perception, Quality of Life, and Behavioral and Objective Measures of Frequency Change Detection.Frontiers in human neuroscience · 2020Article
- The Effect of Side of Implantation on the Cortical Processing of Frequency Changes in Adult Cochlear Implant Users.Frontiers in neuroscience · 2020Article
- Musical Sound Quality as a Function of the Number of Channels in Modern Cochlear Implant Recipients.Frontiers in neuroscience · 2019Article
- Early Gap Detection Threshold Predicts Late Speech Perception in Cochlear Implant Users.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-facialeArticle
- Measuring Spectrotemporal Sensitivity in Cochlear Implant Users With a Reaction-Time Paradigm: A Comparison of Two Implementations.Trends in hearingArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Dynamic frequency changes in sound provide critical cues for speech perception. Most previous studies examining frequency discrimination in cochlear implant (CI) users have employed behavioral tasks in which target and reference tones (differing in frequency) are presented statically in separate time intervals. Participants are required to identify the target frequency by comparing stimuli across these time intervals. However, perceiving dynamic frequency changes in speech requires detection of within-interval frequency change. This study explored the relationship between detection of within-interval frequency changes and speech perception performance of CI users. Frequency change detection thresholds (FCDTs) were measured in 20 adult CI users using a 3-alternative forced-choice (3AFC) procedure. Stimuli were 1-sec pure tones (base frequencies at 0.25, 1, 4 kHz) with frequency changes occurring 0.5 s after the tone onset. Speech tests were 1) Consonant-Nucleus-Consonant (CNC) monosyllabic word recognition, 2) Arizona Biomedical Sentence Recognition (AzBio) in Quiet, 3) AzBio in Noise (AzBio-N, +10 dB signal-to-noise/SNR ratio), and 4) Digits-in-noise (DIN). Participants' subjective satisfaction with the CI was obtained. Results showed that correlations between FCDTs and speech perception were all statistically significant. The satisfaction level of CI use was not related to FCDTs, after controlling for major demographic factors. DIN speech reception thresholds were significantly correlated to AzBio-N scores. The current findings suggest that the ability to detect within-interval frequency changes may play an important role in speech perception performance of CI users. FCDT and DIN can serve as simple and rapid tests that require no or minimal linguistic background for the prediction of CI speech outcomes.
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