Advancements in Forensic Voice Analysis: Legal Frameworks and Technology Integration

Jain, Pragati and Chinmayee, Pragna and Kaur, Kamaljeet and Chaudhary, Shefali and Kaur, Kulwinder and Karunya, S. (2024) Advancements in Forensic Voice Analysis: Legal Frameworks and Technology Integration. Asian Journal of Advances in Research, 7 (1). pp. 369-384.

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Abstract

Forensic acoustics, specifically forensic phonetics, plays a crucial role in legal investigations. It aids in speaker identification, tape authenticity, and analyzing contested statements. In India, the legal framework for forensic voice analysis has evolved through amendments to the Indian Evidence Act and key judicial rulings, although specific legislation for voice sample testing is lacking. Internationally, voice identification has long-standing applications with significant advancements in voice analysis technology. Technologies such as Layered Voice Analysis (LVA) and Phonexia Voice Biometrics Solution demonstrate high accuracy in identifying individuals and uncovering emotional cues, meeting international standards for court admissibility. AI and machine learning enhance forensic voice recognition by providing rapid and accurate analysis, addressing traditional limitations. Ongoing research, including Muiredach O’Riain's project on machine learning for forensic audio classification, underscores AI's innovative potential in forensic applications. Modern statistical techniques like Bayesian analysis offer more reliable results, despite challenges such as voice alterations due to illness and diverse interpretations of sound analysis methods. Advancements in technology and AI integration present promising avenues for improving the accuracy and reliability of forensic voice analysis in legal contexts. Continued research and development are necessary to maximize its effectiveness in the pursuit of justice.

Item Type: Article
Subjects: Open Digi Academic > Multidisciplinary
Depositing User: Unnamed user with email support@opendigiacademic.com
Date Deposited: 26 Jul 2024 07:07
Last Modified: 26 Jul 2024 07:07
URI: http://publications.journalstm.com/id/eprint/1486

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