A Fuzzy Training Framework for Controllable Sequence-to-Sequence Generation-Reference-Cited by-同舟云学术

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A Fuzzy Training Framework for Controllable Sequence-to-Sequence Generation

Published:2022 Issue: Volume:10 Page:92467-92480
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Li Jiajia¹,Wang Ping²,Li Zuchao²^ORCID,Liu Xi³,Utiyama Masao⁴^ORCID,Sumita Eiichiro⁴^ORCID,Zhao Hai⁵^ORCID,Ai Haojun²

Affiliation:

1. Music School, Hankou University, Wuhan, China

2. Wuhan University, Wuhan, China

3. Wuhan Conservatory of Music, Wuhan, China

4. National Institute of Information and Communications Technology, Kyoto, Japan

5. Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09867990.pdf?arnumber=9867990

Reference65 articles.

1. Conditional LSTM-GAN for Melody Generation from Lyrics

2. Neural Melody Composition from Lyrics

3. Rapformer: Conditional rap lyrics generation with denoising autoencoders;nikolov;Proc INLG,2020

4. Generation of Hip-Hop Lyrics with Hierarchical Modeling and Conditional Templates

5. Youling: an AI-assisted Lyrics Creation System

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