Prototyping GPT-3-based Method for Controlling Generation of Lyrics and Chords According to User's Intention

Abstract

We aim to develop a GPT-3-based method for generating songs with the atmosphere and concept intended by the user. Although it has been possible to generate song lyrics by giving a fictitious artist name and song title to GPT-3, a method to control the mood and concept of the generated lyrics according to the user's intention has not been established. In this study, we fine-tune the pre-trained model of GPT-3 to generate lyrics and chord progression with the mood and concept of the song as intended by the user by inputting keywords and explanatory text that represent the mood and concept. Furthermore, as a concrete case study, we verify whether the proposed method can generate songs that reflect the characteristics of local regions in order to apply it to regional development.