Audio signal quality enhancement using multi-layered convolutional neural network based auto encoder–decoder

In this research article, a multi-layered convolutional neural network (MLCNN) based auto-CODEC for audio signal enhancement which is utilizing the Mel-frequency cepstral coefficients (MFCC) has been proposed. The proposed MLCNN takes the input as MFCC with different frames from the noise contaminat...

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Veröffentlicht in:	International journal of speech technology Jg. 24; H. 2; S. 425 - 437
Hauptverfasser:	Raj, Shivangi, Prakasam, P., Gupta, Shubham
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.06.2021 Springer Nature B.V
Schlagworte:	Artificial Intelligence Artificial neural networks Codec Coders Engineering Intelligibility Model accuracy Multilayers Neural networks Signal quality Signal to noise ratio Signal,Image and Speech Processing Social Sciences Speech Speech perception Audio signal quality Auto encoder–decoder MFCC Convolutional neural network
ISSN:	1381-2416, 1572-8110
Online-Zugang:	Volltext
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