Speech Production Quality of Cochlear Implant Users with Respect to Duration and Onset of Hearing Loss

Abstract

Purpose: To assess whether postlingual onset and shorter duration of deafness before cochlear implant (CI) provision predict higher speech intelligibility results of CI users. Methods: For an objective judgement of speech intelligibility, we used an automatic speech recognition system computing the word recognition rate (WR) of 50 adult CI users and 50 age-matched control individuals. All subjects were recorded reading a standardized text. Subjects were divided into three groups: pre- or perilingual deafness (A), both >2 years before implantation, postlingual deafness <2 years before implantation (B), or postlingual deafness >2 years before implantation (C). Results: CI users with short duration of postlingual deafness (B) had a significantly higher WR (median 74%) than CI users with long duration of postlingual deafness (C; 68%, p < 0.001) or pre-/perilingual onset (A; 56%, p < 0.001). Compared to their control groups only CI users with short duration of postlingual deafness reached similar WR, others showed significantly lower WR. Other factors such as hearing loss onset, duration of CI use, or duration of amplified hearing showed no consistent influence on speech quality. Conclusions: The speech production quality of adult CI users shows dependencies on the onset and duration of deafness. These features need to be considered while planning rehabilitation.

„Verstehen mich mit der Maske noch alle?“

“…In einer akustisch abgeschirmten Hörprüfkabine wurden 10 Probanden ohne Sprech- oder Stimmstörung sowohl ohne Atemschutzmaske als auch mit einer chirurgischen oder einer FFP2-Maske beim Vorlesen eines Standardtextes digital aufgezeichnet. Zur Messung der Sprachqualität wurde eine etablierte, für wissenschaftliche Zwecke eingesetzte Methode gewählt [ 8 , 9 , 10 ].…”

Phone-Attribute Posteriors to Evaluate the Speech of Cochlear Implant Users

“…In the literature only one study had considered automatic speech analysis of pre-and postlingual CI users. In [9], a study was presented to evaluate the speech intelligibility of CI users. Speech recordings from 50 healthy speakers and 50 CI users (14 prelingual) were considered.…”

Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users

“…In the literature, few studies have addressed acoustic analysis of speech of CI users by implementing machine learning methods. In [2] speech intelligibility of 50 CI users is evaluated using an automatic speech recognition system and compared with 50 Healthy Controls (HC). Recently in [3] automatic classification using Support Vector Machines (SVM) between 20 CI users and 20 healthy speakers was performed in order to evaluate articulation disorders considering acoustic features.…”