An intelligent speech enhancement model using enhanced heuristic-based residual convolutional neural network with encoder-decoder architecture

As the listening capacity exists in humans, they are facing the critical issues of understanding the speeches even in the presence of some background or other noises in the world. To diminish the noises, Speech Enhancement (SE) is the process of improving the quality of the speech signal by applying...

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Vydáno v:	International journal of speech technology Ročník 27; číslo 3; s. 637 - 656
Hlavní autoři:	Balasubrahmanyam, M., Valarmathi, R. S.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.09.2024 Springer Nature B.V
Témata:	Acknowledgment Algorithms Artificial Intelligence Artificial neural networks Background noise Computation Deep learning Encoders-Decoders Engineering Error analysis Hearing aids Heuristic Intelligence Intelligibility Learning Machine learning Neural networks Noise Performance evaluation Railway stations Restaurants Root-mean-square errors Signal quality Signal,Image and Speech Processing Social Sciences Speech Speech enhancement Speech processing Speech recognition Speeches Supervised learning Voice recognition Work Speech enhancement Divergent noise signals Speech signal Adaptive residual convolutional neural networks with encoder-decoder Random revised drawer algorithm
ISSN:	1381-2416, 1572-8110
On-line přístup:	Získat plný text
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