Calibrated Acoustic Evidence: Legal and Methodological Advances in Forensic Voice Comparison for Indonesia
Year: 2024
Type: article
Abstract: Forensic voice comparison (FVC) is gaining global recognition as a scientific method for speaker identification in legal proceedings. In Indonesia, however, the application of FVC remains underdeveloped, despite increasing reliance on digital and audio based evidence in criminal cases. This study presents a legally and methodologically robust framework for implementing FVC within the Indonesian judicial context. The research integrates Indonesian legal standards (KUHAP Articles 183–184, UU ITE) with international forensic protocols, including ISO/IEC 27037 for digital evidence handling. A combination of acoustic features MFCCs, F0, formants, and VTLN was extracted from disputed and reference voice samples. Likelihood ratios (LRs) were calculated using Gaussian Mixture Models, with score calibration via logistic regression. Results showed mean log LR values of 2.1 for genuine trials and –1.8 for impostor trials, with an ROC AUC of 0.91. Visual tools, including Tippett plots and ROC curves, were used to interpret and communicate evidence reliability. The findings confirm that calibrated, probabilistic FVC methods are feasible and legally admissible in Indonesia. However, challenges remain in handling low quality recordings, maintaining chain of custody, and bridging communication gaps between scientific experts and legal practitioners. The study recommends structured training, standardized protocols, and the use of visual aids to enhance evidentiary transparency. This framework lays the foundation for a scalable, court ready FVC system aligned with national law and global best practices. It supports interdisciplinary cooperation aimed at strengthening Indonesia’s forensic infrastructure.
Author: Redjeki Agoestyowati
Institution: Institut Ilmu Sosial dan Manajemen STIAMI
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7087463382