Abstract

System and method are disclosed to detect spam in outgoing or incoming calls on a telephone device. The system includes a server running a machine-learning algorithm coupled to a spam detection service running on the device that detects spam during an outgoing or incoming call. When the user places a call; the device listens to the conversation and extracts identifiable characteristics through acoustic characterization. These characteristics constituting a signature are received by the spam detection service to identify spam. If a spam call is detected, the user is warned through an audio cue during the call and ends the call. If spam is not detected, the user continues the conversation. After the call, user is allowed to assign a spam rating. The spam rating and acoustic signature entry are sent to the server to improve the machine learning algorithm. The disclosed method of detecting spam calls helps users save money.

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