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Audio Segmentation Techniques and Applications Based on Deep Learning.

Authors :
Aggarwal, Shruti
G, Vasukidevi
Selvakanmani, S.
Pant, Bhaskar
Kaur, Kiranjeet
Verma, Amit
Binegde, Geleta Negasa
Source :
Scientific Programming. 8/19/2022, p1-9. 9p.
Publication Year :
2022

Abstract

Audio processing has become an inseparable part of modern applications in domains ranging from health care to speech-controlled devices. In automated audio segmentation, deep learning plays a vital role. In this article, we are discussing audio segmentation based on deep learning. Audio segmentation divides the digital audio signal into a sequence of segments or frames and then classifies these into various classes such as speech recognition, music, or noise. Segmentation plays an important role in audio signal processing. The most important aspect is to secure a large amount of high-quality data when training a deep learning network. In this study, various application areas, citation records, documents published year-wise, and source-wise analysis are computed using Scopus and Web of Science (WoS) databases. The analysis presented in this paper supports and establishes the significance of the deep learning techniques in audio segmentation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10589244
Database :
Academic Search Index
Journal :
Scientific Programming
Publication Type :
Academic Journal
Accession number :
158630371
Full Text :
https://doi.org/10.1155/2022/7994191