Lightweight real-time recurrent models for speech enhancement and automatic speech recognition

Traditional recurrent neural networks (RNNs) encounter difficulty in capturing long-term temporal dependencies. However, lightweight recurrent models for speech enhancement are important to improve noisy speech, while being computationally efficient and able to capture long-term temporal dependencie...

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Bibliographic Details
Main Authors: Dhahbi, Sami, Saleem, Nasir, Gunawan, Teddy Surya, Bourouis, Sami, Ali, Imad, Trigui, Aymen, Algarni, Abeer D
Format: Article
Language:English
English
English
Published: Universidad Internacional de la Rioja 2024
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Online Access:http://irep.iium.edu.my/113757/1/113757_Lightweight%20real-time%20recurrent%20models.pdf
http://irep.iium.edu.my/113757/2/113757_Lightweight%20real-time%20recurrent%20models_SCOPUS.pdf
http://irep.iium.edu.my/113757/3/113757_Lightweight%20real-time%20recurrent%20models_WOS.pdf
http://irep.iium.edu.my/113757/
https://www.ijimai.org/journal/bibcite/reference/3450
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