@Article{aev:2022-10.55753/aev.v37e54.194,
title = {The effects of anger on automated long-term-spectra based speaker-identification},
author = {Ortega-Rodríguez, M. AND Solís-Sánchez, H. AND Valverde-Méndez, D. AND Venegas-Li, A.},
journal = {Acústica e Vibrações},
year = {2022},
issn = {1983-442X, 2764-3611},
month = {dezembro},
number = {54},
pages = {53--60},
volume = {37},
doi = {10.55753/aev.v37e54.194},
publisher = {Sociedade Brasileira de Acústica},
keywords = {automated speaker identification, long term spectra, forensic acoustics, emotional distortions, anger},
abstract = {Forensic speaker identification has traditionally considered approaches based on long-term (a few tens of seconds) spectra analysis as especially robust. This is because they work well for short recordings, are not sensitive to changes in the intensity of the sample, and continue to function in the presence of noise and limited passband. Because of this, the long-term spectra approach is one of the preferred tools for forensic speaker identification, in addition to formant analysis, speed of speech, and determination of the fundamental frequency. However, we find that anger induces a significant distortion of the acoustic signal for long-term spectra analysis purposes. Even moderate anger offsets speaker identification results by 33\% in the direction of a different speaker altogether (in the space of sample correlations). Therefore, caution should be exercised when applying this tool.},
}