Abstract
Difficulty in speech discrimination is a major complaint among post lingually deafened adults, which are cochlear implant (CI) users. Consequently, it is important to study the factors that offer positive post-operative outcomes in order to get the most out of this technology. Thus, many clinicians tend to orient the implanted toward the auditory training program with the aim of teaching them to make perceptual distinctions about sounds that are presented systematically. Therefore, a systematic review was performed to examine the influence of aural rehabilitation on post lingually deafened cochlear implant users’ speech recognition with an eye towards reaching its full potential. A total of 20 articles was used in this review, chosen from PubMed, Science Direct, semantic scholar, international journal of audiology, and journal of speech, language, and hearing research. It was therefore concluded from the analysis of the previous studies that the auditory training may be advantageous when it considers the individual’s own characteristics towards designing a proper auditory training program while tracking his/her progress throughout this period. Furthermore, choosing between clinician-directed training and computer-based home training or a combination of both is essential, considering the patient and the clinician’s preferences. Not to mention the high importance of choosing a processing strategy that helps differentiate between the sound cues. It may also be beneficial to train the cochlear implant users on environmental sound identification as well as speech recognition or speech tracking to recognize them better. Auditory rehabilitation could be more valuable when provided in the long-term and when conducted in more realistic situations that resemble real-life environments. In order to achieve the desired results, future studies should focus on sample size adjustments, including less heterogeneity among the participants, while conducting long-term training suitable for each patient along with the proper processing strategy.
Abbreviations:CI: Cochlear Implant; HINT: Hearing in Noise Test; SPIN: Speech in Noise; GBI: Glasgow Benefit Inventory; BKB: Bamford-Kowal-Bench; SNR: Signal-to-Noise Ratio; VDS: Visual Digit Span; ADS: Auditory Digit Span; VER: Vocation Emotion Recognition; MCI: Melodic Contour Identification; FEST: Familiar Environmental Sound Test; CNC: Consonant-Nucleus-Consonant; NNSE: Neural Network based Speech Enhancement
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https://scholar.google.com/citations?view_op=view_citation&hl=en&user=dMOUw-wAAAAJ&cstart=20&pagesize=80&citation_for_view=dMOUw-wAAAAJ:d4tt_xEv1X8C
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