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Active Noise Cancellation in Microsoft Teams Using AI & NLP Powered Algorithms


Affiliations
1 School of Computer and Information Science, University of the Cumberlands, KY, United States
2 Department of Computer and Information Science, University of the Cumberlands, KY, United States
 

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, NLP, Microsoft Teams, Speech Identification, Video Call, Video Signal Data, Machine Learning.
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Abstract Views: 219

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  • Active Noise Cancellation in Microsoft Teams Using AI & NLP Powered Algorithms

Abstract Views: 219  |  PDF Views: 109

Authors

Pawankumar Sharma
School of Computer and Information Science, University of the Cumberlands, KY, United States
Bibhu Dash
Department of Computer and Information Science, University of the Cumberlands, KY, United States

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, NLP, Microsoft Teams, Speech Identification, Video Call, Video Signal Data, Machine Learning.

References