Forensic Speaker Comparison Using Evidence Interval in Full Bayesian Significance Test
Joint Authors
Silva, Adelino P.
Vieira, Maurílio N.
Barbosa, Adriano V.
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-24
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper describes the application of a full Bayesian significance test (FBST) to compute evidence intervals in forensic speaker comparison (FSC).
In the FBST approach, the challenge is to apply the test to a large number of observations and to formulate an equation to solve the test quickly.
The contribution of the present work is that it proposes an application of the FBST to FSC and develops a method to calculate the FBST for the distribution of expected values (mean) with unknown variance without using Monte Carlo Markov chains (MCMC).
Comparisons with other interval inference methodologies indicate that the evidence interval size is 49% greater than that computed with the Gosset approach.
The evidence interval presented 71% fewer classification errors than the punctual inference did for the signal-to-noise ratio (SNR) of 17 dB.
American Psychological Association (APA)
Silva, Adelino P.& Vieira, Maurílio N.& Barbosa, Adriano V.. 2020. Forensic Speaker Comparison Using Evidence Interval in Full Bayesian Significance Test. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1194117
Modern Language Association (MLA)
Silva, Adelino P.…[et al.]. Forensic Speaker Comparison Using Evidence Interval in Full Bayesian Significance Test. Mathematical Problems in Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1194117
American Medical Association (AMA)
Silva, Adelino P.& Vieira, Maurílio N.& Barbosa, Adriano V.. Forensic Speaker Comparison Using Evidence Interval in Full Bayesian Significance Test. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1194117
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194117