NSE-CATNet: Deep Neural Speech Enhancement Using Convolutional Attention Transformer Network-Reference-Cited by-同舟云学术

NSE-CATNet: Deep Neural Speech Enhancement Using Convolutional Attention Transformer Network

Published:2023 Issue: Volume:11 Page:66979-66994
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Saleem Nasir¹^ORCID,Gunawan Teddy Surya²^ORCID,Kartiwi Mira³^ORCID,Nugroho Bambang Setia⁴,Wijayanto Inung⁴

Affiliation:

1. Department of Electrical Engineering, Faculty of Engineering and Technology, Gomal University, Dera Ismail Khan, Pakistan

2. Electrical and Computer Engineering Department, International Islamic University Malaysia (IIUM), Kuala Lumpur, Malaysia

3. Information Systems Department, International Islamic University Malaysia (IIUM), Kuala Lumpur, Malaysia

4. School of Electrical Engineering, Telkom University, Bandung, Indonesia

Funder

Telkom University Research Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10168245.pdf?arnumber=10168245

Reference71 articles.

1. A New Ratio Mask Representation for CASA-Based Speech Enhancement

2. An integrated CNN-GRU framework for complex ratio mask estimation in speech enhancement;hasannezhad;Proc Asia–Pacific Signal Inf Process Assoc Annu Summit Conf (APSIPA ASC),2020

3. Performance analysis of ideal binary masks in speech enhancement

4. Evaluation of Objective Quality Measures for Speech Enhancement

5. On Training Targets for Supervised Speech Separation

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