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Does the Remote Microphone Still Outperform the Pre-Processing Algorithms? A Group Study in Adult Nucleus Recipients

Authors :
Francesco Lazzerini
Luca Baldassari
Adriana Angileri
Luca Bruschini
Stefano Berrettini
Francesca Forli
Source :
Journal of Otorhinolaryngology, Hearing and Balance Medicine, Vol 4, Iss 2, p 9 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Despite the evolution of hearing aids and cochlear implants, noisy environments are reportedly still an important hurdle for persons with hearing loss, especially in the process of speech recognition. The development of pre-processing algorithms and the pairing with a wireless device can bring relief to this situation, but it is still under scrutiny whether one or the other is more effective. The purpose of this study was to compare the benefits of speech recognition in a noisy environment by recipients of cochlear implants when using the pre-processing automatic algorithms or when using a wireless microphone. Twenty-nine participants were selected, aged 14 to 83, suffering from sensorineural hearing loss and recipients of cochlear implants for at least 6 months. The proprietary Cochlear Limited SCAN technology uses pre-processing algorithms to attenuate various noises; the wireless device MiniMic2 uses a 2.4 GHz connection to facilitate communications between the recipient and the signal source. Participants were asked to repeat 20 sentences randomly generated by the adaptive Italian Matrix Sentence Test, first while using the SCAN technology and then with the wireless MiniMic2. Both signal and noise were administered through a single loudspeaker set 1 m away from the subject. Significantly better results in speech recognition of noise were achieved with the wireless MiniMic2 when compared to the SCAN technology.

Details

Language :
English
ISSN :
2504463X
Volume :
4
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Otorhinolaryngology, Hearing and Balance Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.94f403d882d84708b0f81c40f17ee7e7
Document Type :
article
Full Text :
https://doi.org/10.3390/ohbm4020009