Open AccessEffective speaker spotting for watch‐list detection of fraudsters in telephone banking
Author(s) -
Gunson Nancie,
Marshall Diarmid,
Jack Mervyn
Publication year - 2015
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
eISSN - 2047-4946
pISSN - 2047-4938
DOI - 10.1049/iet-bmt.2013.0060
Subject(s) - computer science , spotting , identification (biology) , set (abstract data type) , speaker recognition , speech recognition , computer security , artificial intelligence , botany , biology , programming language
This study describes a special‐case application of speaker recognition in open‐set speaker‐identification mode, which nonetheless has wide applicability. Watch‐list based speaker spotting in telephone banking can potentially provide valuable protection against ‘known’ fraudsters with access to stolen customer details. In this study, the detection of known fraudsters in a telephone banking service using commercial off‐the‐shelf verification engines is described. A new ‘delta scoring’ method for watch‐list detection is proposed based on using the genuine customer model as a reference. The approach combines for the first time speaker recognition in both verification and identification mode. Empirical experiment results show a significant gain in performance using the new method.