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.

Machine learningNatural languageSpeechKnowledge representationPlanningH04M 3/493G06N 3/08G06N 3/09G06N 20/00H04M 3/436H04M 2203/6027

AI classification

Natural language1.00
Speech1.00
Machine learning0.99
Knowledge representation0.99
Planning0.90
Evolutionary computation0.22
AI hardware0.01
Vision0.00

Ownership

T-MOBILE USA, INC.

assignment · 568240594

Assignors

SERBAN, OVIDIU

On an employer assignment, the assignors are typically the inventors.

From the same owner

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