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

• 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
• Subjects: TK7885 Computer engineering
• 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

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...