Fraud detection in telephone conversations for financial services using linguistic features

Autor: Bajaj, Nikesh, Constance, Tracy Goodluck, Rajwadi, Marvin, Wall, Julie, Moniri, Mansour, Glackin, Cornelius, Cannings, Nigel, Woodruff, Chris, Laird, James

Detecting the elements of deception in a conversation is one of the most challenging problems for the AI community. It becomes even more difficult to design a transparent system, which is fully explainable and satisfies the need for financial and leg

Externí odkaz: http://arxiv.org/abs/1912.04748

Speaker Recognition using Multiple X-Vector Speaker Representations with Two-Stage Clustering and Outlier Detection Refinement

Autor: Shrestha, Roman, Glackin, Cornelius, Wall, Julie, Cannings, Nigel, Rajwadi, Marvin, Kada, Satya, Laird, James, Laird, Thea, Woodruff, Chris

Publikováno v: 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)

This paper presents a novel Variational Bayes x-vector Voice Print Extraction (VBxVPE) system, capable of capturing vocal variations using multiple x-vector representations with two-stage clustering and outlier detection for robust speaker recognitio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5a1b2b4a8a5044a3ed2de5b8217c15b