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Using Artificial Intelligence to Filter out Barking, Typing, and other Noise from Video Calls in Microsoft Teams

Authors

Pawankumar Sharma, Bibhu Dash, University of the Cumberlands, USA

Abstract

The normal method for analyzing technology is formulating many search queries to extract patent datasets and filter the data physically. The purpose of filtering the collected data is to remove noise to guarantee accurate information analysis. With the advancement in technology and machine learning, the work of physical analysis of the patent can be programmed so the system can remove noise depending on the results based on the previous data. Microsoft team generates a new artificial intelligence model that provides solutions on how individuals respond to speakers. Microsoft team, workplace, Facebook, and Google collected data from many active users hence developing artificial intelligence to minimize distracting background noise, barking and typing during the call.

Keywords

Artificial intelligence, Microsoft teams, speech identification, video call, video signal data, machine learning, and data sets