TY - GEN
T1 - Rap Lyrics Generation Using Vowel GAN
AU - Miyano, Tomoya
AU - Saito, Hiroaki
N1 - Publisher Copyright:
© 2020, Springer Nature Singapore Pte Ltd.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Despite the success of recent rap and poetry generations using neural models, many of them do not consider vowels of the entire lyrics. Also, in many cases it is virtually impossible to generate completely new lyrics, because only existing rap lyrics are used as data sets. This paper proposes a new method of rap lyrics generation using a large amount of text such as novels in addition to rap lyrics. We divided the generation of rap lyrics into two steps; first, Generative Adversalial Net (GAN) generates rhymes and flows. Second, sequence-to-sequence converts them into rap lyrics. In addition, this method refers to the generation style of rap songs. In other words, they determine the music and rhythm first and apply the words second. We evaluated our method based on BLEU that can be measured mechanically.
AB - Despite the success of recent rap and poetry generations using neural models, many of them do not consider vowels of the entire lyrics. Also, in many cases it is virtually impossible to generate completely new lyrics, because only existing rap lyrics are used as data sets. This paper proposes a new method of rap lyrics generation using a large amount of text such as novels in addition to rap lyrics. We divided the generation of rap lyrics into two steps; first, Generative Adversalial Net (GAN) generates rhymes and flows. Second, sequence-to-sequence converts them into rap lyrics. In addition, this method refers to the generation style of rap songs. In other words, they determine the music and rhythm first and apply the words second. We evaluated our method based on BLEU that can be measured mechanically.
KW - GAN
KW - Rap song
KW - Sequence-to-sequence
UR - http://www.scopus.com/inward/record.url?scp=85088502670&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85088502670&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-6168-9_26
DO - 10.1007/978-981-15-6168-9_26
M3 - Conference contribution
AN - SCOPUS:85088502670
SN - 9789811561672
T3 - Communications in Computer and Information Science
SP - 307
EP - 318
BT - Computational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers
A2 - Nguyen, Le-Minh
A2 - Tojo, Satoshi
A2 - Phan, Xuan-Hieu
A2 - Hasida, Kôiti
PB - Springer
T2 - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019
Y2 - 11 October 2019 through 13 October 2019
ER -