Deutsche Telekom has filed a patent for systems and methods to detect scam callers using machine learning and an Interactive Voice Response model. The technology simulates subscriber speech to engage with callers and classify them as scam or non-scam, allowing for alerts or call disconnections if necessary. GlobalData’s report on Deutsche Telekom gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Deutsche Telekom, Payment actuated vending was a key innovation area identified from patents. Deutsche Telekom's grant share as of January 2024 was 66%. Grant share is based on the ratio of number of grants to total number of patents.
Automated detection of scam calls using machine learning
A newly filed patent (Publication Number: US20240040038A1) describes a computing system designed for the automated detection of scam calls. The system includes at least one hardware processor and memory storing instructions that enable the system to receive phone calls routed away from a subscriber, simulate the subscriber's speech to elicit responses from the caller, classify the caller as a scam or non-scam based on the responses, and process the call accordingly. This processing may involve automatically disconnecting the call if the caller is identified as a scammer or displaying a notice on the subscriber's mobile device.
Furthermore, the patent outlines a method and computer-readable medium storing instructions for implementing the automated scam call detection system. The method involves receiving audio/video communications routed away from a subscriber, simulating the subscriber's speech to elicit responses, classifying the caller as a scam or non-scam based on the responses, and processing the communication accordingly. This processing may include automatically disconnecting the communication or displaying a notice on the subscriber's mobile device. The system also generates a database entry to track scam callers and can route future communications away from these identified scammers based on the database entry. The classification of the caller as a scam or non-scam is determined using subscriber-specific information stored in the subscriber's profile.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
