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Abstract

Humans can predict when someone is about to say something profane by recognizing various social cues. Utilizing machine learning algorithms, this solution can mimic human prediction and provide a percentage of confidence on when a profane incident will occur.

Some important key phrases include:

  • Censorship event: a point in time where the system activates a mechanism where the profane word is not heard.
  • Statistical confidence: an output percentage that the neural network provides to decide on whether to execute a censorship event.
  • Natural Language Processing: a way for the system to mimic how a human understands communication via words or other social cues.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.

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