Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement

Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement

Deep learning (DL) networks have grown into powerful alternatives for speech enhancement and have achieved excellent results by improving speech quality, intelligibility, and background noise suppression. Due to high computational load, most of the DL models for speech enhancement are difficult to i...

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Bibliographic Details
Main Authors: Fazal-E -Wahab, Zhongfu Ye, Nasir Saleem, Hamza Ali, Imad Ali
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2025-01-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
convolutional gated recurrent unit (convolutional gru)
deep learning
intelligibility
long short term memory (lstm)
speech enhancement
Online Access:https://www.ijimai.org/journal/bibcite/reference/3324

Internet

https://www.ijimai.org/journal/bibcite/reference/3324

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