Idea 1: Masked Face Detection:
Introduction: Due to the fact that the virus that causes COVID-19 is spread mainly from person to person through respiratory droplets produced when an infected person coughs, sneezes, or talks, it is important that people should wear masks in public places. However, it would be difficult to keep track of a large number of people at the same time. Hence, my idea is to utilize machine learning to detect if a person is wearing a mask or not. Hopefully, this idea can help reduce the spread of the coronavirus.
Idea 2: Speaker Recognition:
Introduction: BookTubeSpeech is a newly released dataset for speech analysis problems. The dataset contains 8,450 YouTube videos (7.74 min per video on average) that each contains a single unique speaker. Not much work on speaker recognition has been done using this dataset. My work is to provide one of the first baselines on this dataset for speaker recognition / speaker verification.
Idea 3: Sport players prediction result using machine learning
Introduction: “How many yards will an NFL player gain after receiving a handoff?” I will be attending a competition on Kaggle. During the process, Kaggle would provide a dataset of players from different teams, the team, plays, players’ stats including position and speed to analyze and generalize a model of how far an NFL player can run after receiving the ball.