Lyrics-Conditioned Neural Melody Generation
Generating 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.
WOS:000611566100058
2020-01-01
978-3-030-37734-2
978-3-030-37733-5
Cham
Lecture Notes in Computer Science
11962
709
714
REVIEWED
Event name | Event place | Event date |
Daejeon, SOUTH KOREA | Jan 05-08, 2020 | |