Fundamental study on ambient noise reduction for analysis of hitting sound of professional baseball players

Abstract

In recent years, the sound of a hitting ball during a baseball game has focused attention on the American Major League Baseball and Japanese professional baseball. It is reported that information such as the direction and distance of a batted ball can be detected from the sound. The sounds of players hitting the ball are sometimes expressed using various onomatopoeic. In our previous study, we recorded the sound of a baseball hit during hitting practice for players of a university baseball team in the Tokyo metropolitan area in Japan. Relationships between the acoustic characteristics of the sound and the distance and direction of the ball were clarified. In this research, acoustic analysis of professional baseball players' batted ball sounds from Youtube and other videos is used to identify the acoustic features and characteristics of the batted ball. This paper describes the method and accuracy of noise removal around the hitting sound extracted from the video using a convolutional neural network with images.