Detecting Deepfake Voices Using a Novel Method for Authenticity Verification in Voice-Based Communication

Title

Detecting Deepfake Voices Using a Novel Method for Authenticity Verification in Voice-Based Communication

Creator

Kansara A.; Kumari P.; Prathap B.R.

Description

The widespread use of deepfake technology in recent years has given rise to grave worries about the alteration of audio-visual material. The integrity of voice-based communication is particularly vulnerable to the threat posed by deepfake voice synthesis. The development of cutting-edge methods for the identification of deepfake voices is examined in this paper, which also offers a thorough analysis of current approaches, their advantages, and disadvantages. The research presents a novel method for detecting deepfakes in voice recordings that uses signal processing, machine learning, and audio analysis to separate synthetic voices from authentic voices. By achieving superior accuracy in differentiating between real and deepfake voices, and proposed method supplies a strong barrier against the misuse of voice synthesis technology for malicious purposes, also go over the research some of the possible uses for this technology, like voice authentication system security and social media platform content moderation. The paper's insights will support continued efforts to strengthen the authenticity of voice communication in the digital age and reduce the risks associated with deepfake voice synthesis. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Source

Lecture Notes in Networks and Systems, Vol-1088 LNNS, pp. 397-405.

Date

2024-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Audio Analysis; Deepfake Voice; Machine Learning; Signal Processing; Social Media; Voice Authentication System; Voice Synthesis

Coverage

Kansara A., Computer Science and Engineering (Specialization in Data Science), Christ University, Bangalore, India; Kumari P., Computer Science and Engineering (Specialization in Data Science), Christ University, Bangalore, India; Prathap B.R., Computer Science and Engineering (Specialization in Data Science), Christ University, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-303170017-0

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-3-031-70018-7_45

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203590498&doi=10.1007%2f978-3-031-70018-7_45&partnerID=40&md5=faf012273e98d173a581ada33c30d478