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

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.