Yu, YiHarscoet, FlorianCanales, SimonReddy, Gurunath M.Tang, SuhuaJiang, Junjun2021-03-262021-03-262021-03-262020-01-0110.1007/978-3-030-37734-2_58https://infoscience.epfl.ch/handle/20.500.14299/176747WOS:000611566100058Generating melody from lyrics to compose a song has been a very interesting research topic in the area of artificial intelligence and music, which tries to predict generative music relationship between lyrics and melody. In this demonstration paper, by exploiting a large music dataset with 12,197 pairs of English lyrics and melodies, we develop a lyrics-conditioned AI neural melody generation system that consists of three components: lyrics encoder network, melody generation network, and MIDI sequence tuner. Most importantly, a Long Short-Term Memory (LSTM)-based melody generator conditioned on lyrics, is trained by applying a generative adversarial network (GAN), to generate a pleasing and meaningful melody matching the given lyrics. Our demonstration illustrates the effectiveness of the proposed melody generation system.Computer Science, Artificial IntelligenceComputer Science, Software EngineeringImaging Science & Photographic TechnologyComputer Sciencelyrics-conditioned melody generationlong short-term memorygenerative adversarial networktext::conference output::conference proceedings::conference paper