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Automatic call classification and screening

A call counting, computer technology, applied in the direction of automatic exchange, audio data clustering/classification, instruments, etc., can solve problems such as limiting efficacy

Pending Publication Date: 2022-06-24
GOOGLE LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Many spam callers forge or spoof their numbers, which limits the efficacy of number-based anti-spam tools, such as lists of numbers associated with spam callers

Method used

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  • Automatic call classification and screening
  • Automatic call classification and screening
  • Automatic call classification and screening

Examples

Experimental program
Comparison scheme
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Embodiment Construction

[0025] Some implementations described herein relate to methods, systems, and computer-readable media for generating models of bots and / or spam callers. In some embodiments, call embeddings (spam embeddings) representing calls from bots and / or spam callers are generated. The described embodiments generate garbage embeddings (eg, numerical representations) from audio recordings (eg, a training corpus) using a trained machine learning model. The corpus may include audio recordings of calls or other audio recordings that include spam. For example, spam embeddings are provided from a server to client devices that store garbage embeddings locally.

[0026] Some embodiments described herein relate to methods, systems, and computer-readable media for automatically answering calls and detecting spam calls. When a call is received at the client device, the client device determines whether the call meets auto-answer criteria. If the call meets the auto answer criteria, the call is ans...

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PUM

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Abstract

Embodiments described herein relate to methods, systems, and computer-readable media for automatically answering a call. In some implementations, a method includes receiving, at a client device, a call from a calling device. The method also includes determining whether the call matches an auto-answer criterion based on the identifier related to the call, and responsive to determining that the call matches the auto-answer criterion, answering the call without user input and without a user prompt to the client device. The method further includes generating a call embedding of the call based on the received audio of the call, comparing the call embedding to a junk embedding to determine whether the call is a junk call, and terminating the call in response to determining that the call is a junk call.

Description

[0001] cross reference [0002] This application claims the benefit of US Provisional Application 62 / 937,769, filed November 19, 2019, entitled "Automated Spam Call Detection," which is incorporated herein by reference in its entirety. Background technique [0003] Spam calls, including robocalls, are a large and growing problem. Users in the U.S. receive more than 4 billion robocalls each month. Many spam callers forge or spoof their numbers, which limits the efficacy of number-based anti-spam tools, such as number lists associated with spam callers. [0004] The background description provided herein is for the purpose of generally presenting the context of the disclosure. The work of the inventors of the present invention described in this Background section, together with aspects of the description that may not qualify as prior art at the time of filing, is neither expressly nor implicitly admitted as prior art to the present disclosure . SUMMARY OF THE INVENTION [...

Claims

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Application Information

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IPC IPC(8): G06F16/683H04M3/436H04M3/42
CPCH04M3/42042H04M3/436G06F16/685H04M2201/40H04M2203/2038H04M2203/552G06F16/65G06F16/61G10L15/26H04M3/527
Inventor 约瑟夫·切鲁卡拉保罗·邓禄普张涵夫米洛·斯雷德科夫阿迪提·巴尔加瓦玛丽亚·桑德里科娃古斯塔夫·森顿乌斯曼·阿卜杜拉安德烈斯·卡尔沃布兰登·麦克斯韦丽贝卡·朴智秀·邱柯蒂斯·罗宾逊耶鲁·托马斯理查德·莱德利阿比吉特·沙斯特里阿伊莎·赫瓦佳金娴莎王伟力苏巴什·古塔拉沙尚克·戈亚尔
Owner GOOGLE LLC