Bio‐signal‐processing‐based convolutional neural networks model for music program scene editing.

Summary: Popular songs have evolved from vinyl records (voice files) to music videos. Sound and video can be mixed and presented in such a manner that only sound is heard. Scenes from music programs require continuous editing to maximize audience immersion. Music program scene editing is developed through the expertise of a television program director (PD). The PD considers detailed editing methods by the analyzing lyrics and the singer's choreography to express a song in a rhythmic video. This study presents an algorithm for music program scene editing that determines the size of a shot, evaluating the psychological distance between singer and viewers after measuring the pitch contour of a song. [ABSTRACT FROM AUTHOR]