Speaker Identification from Forensic Phonetics: Application of SplitsTree4 Software for Schematic Organization of Linguistic Data

Peña J.J.; Castillo F.A.T.; Sanchez O.E.C. · Boletin de la Academia Peruana de la Lengua (2022) · DOI: 10.46744/bapl.202201.014

Resumen

This article presents a proposal for the interpretation and organization of the phonetic characteristics of undoubted and doubted samples using SplitsTree4 software for the purpose of clarifying an alleged crime of passive bribery in the exercise of the police function to the detriment of the State. The doubted samples were provided by the Public Prosecutor's Office and the undoubted samples were obtained by means of voice sampling; likewise, data anonymity was chosen. First, each sample's relevant phonetic features were categorized; then, they were assigned a binary value of existence and non-existence; then, the binary information was processed by SplitsTree4 software to regroup the features according to the universe of speakers and show the compatibility between the indicated samples. Finally, the results indicate that the SplitsTree4 software complies with the sorting of phonetic-articulatory data for forensic voice identification. © Copyright 2022 by the Infectious Diseases and Clinical Microbiology Specialty Society of Turkey.

Instituciones: Universidad Nacional Mayor de San Marcos