A deep learning based noise reduction approach to improve speech intelligibility for cochlear implant recipients in the presence of competing speech noise

This paper presents the clinical results of the application of a deep-learning-based noise reduction (NR) approach to improve speech intelligibility for cochlear implant (CI) recipients in the presence of competing speech noise. The deep denoising autoencoder (DDAE) model was used as a representativ...

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Vydané v:	APSIPA ASC 2017 : proceedings, ninth Asia-Pacific Signal and Information Processing Association Annual Summit and Conference : 12-15 December 2017, Kuala Lumpur, Malaysia s. 808 - 812
Hlavní autori:	Syu-Siang Wang, Yu Tsao, Wang, Hsiao-Lan Sharon, Ying-Hui Lai, Li, Lieber Po-Hung
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2017
Predmet:	Auditory system Conferences Speech Speech enhancement Speech recognition
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