S. Tyagi, A. R. Várkonyi-Kóczy, S. Szénási: A Comprehensive Investigation into The Noise Reduction Techniques for Speech. In IEEE 21st World Symposium on Applied Machine Intelligence and Informatics (SAMI 2023) Proceedings. pp. 207-212, 2023. ISBN 979-8-3503-1986-6 link

Abstract: There has been a ton of study on the use of machine learning for speech processing applications, particularly voice recognition, over the past few decades. However, in recent years, research has concentrated on using deep learning for applications that relate to voice. In several applications, including speech, this new branch of machine learning has outperformed others, making it an extremely appealing topic for research. This paper presents a comprehensive review of the studies on deep learning for speech applications that have been carried out since 2017 when deep learning emerged as a new field of machine learning. This evaluation provides a rigorous statistical analysis that was completed by removing certain data from 184 papers published between 2017 and 2022. The findings presented in this paper shed light on the patterns of research in this field and concentrate attention on fresh research areas.