DETECTING SCAM CALLERS USING CONVERSATIONAL AGENT AND MACHINE LEARNING SYSTEMS AND METHODS
Patent №
US 11,463,582
Granted
2022-10-04
Filed 2021
Owner
T-MOBILE USA, INC.
Lab
—
AI components
5
ml · nlp · speech · kr · planning
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
17372337
Systems and methods for detecting indications of a scam caller are disclosed. Call data, such as call audio, is received and used to create a training dataset. Using the training dataset, a machine learning model is trained to detect indications of a scam caller in a phone call. An Interactive Voice Response (IVR) model is trained or configured, using voice samples of speech of a subscriber of a telecommunications service provider, to simulate speech and conversation of the subscriber. A conversational agent is generated using the IVR model and the trained machine learning model. The conversational agent receives a phone call, engages a caller in simulated conversation, and detects indications of whether the caller is a likely scam caller. If the caller is determined to be a likely scam caller, an alert can be generated and/or the call can be disconnected.
AI classification
Ownership
T-MOBILE USA, INC.
assignment · 568240594
Assignors
SERBAN, OVIDIU
On an employer assignment, the assignors are typically the inventors.