TY - GEN
T1 - Lyrics-Conditioned Neural Melody Generation
AU - Yu, Yi
AU - Harscoët, Florian
AU - Canales, Simon
AU - Reddy M, Gurunath
AU - Tang, Suhua
AU - Jiang, Junjun
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Generative adversarial network
KW - Long Short-Term Memory
KW - Lyrics-conditioned melody generation
UR - https://www.scopus.com/pages/publications/85080860196
U2 - 10.1007/978-3-030-37734-2_58
DO - 10.1007/978-3-030-37734-2_58
M3 - 会议稿件
AN - SCOPUS:85080860196
SN - 9783030377335
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 709
EP - 714
BT - MultiMedia Modeling - 26th International Conference, MMM 2020, Proceedings
A2 - Ro, Yong Man
A2 - Kim, Junmo
A2 - Choi, Jung-Woo
A2 - Cheng, Wen-Huang
A2 - Chu, Wei-Ta
A2 - Cui, Peng
A2 - Hu, Min-Chun
A2 - De Neve, Wesley
PB - Springer
T2 - 26th International Conference on MultiMedia Modeling, MMM 2020
Y2 - 5 January 2020 through 8 January 2020
ER -