activity
20172020
most citedConditional LSTM-GAN for Melody Generation from Lyrics

98 citations · 129 across the 9 of their papers we have counts for

collaborators

11 papers

cs.AI2020★ 3 cited

Conditional Hybrid GAN for Sequence Generation

Yi Yu, Abhishek Srivastava, Rajiv Ratn Shah

Conditional sequence generation aims to instruct the generation procedure by conditioning the model with additional context information, which is a self-supervised learning issue (…

cs.CV2020★ 3 cited

PAI-BPR: Personalized Outfit Recommendation Scheme with Attribute-wise Interpretability

Dikshant Sagar, Jatin Garg, Prarthana Kansal +3

Fashion is an important part of human experience. Events such as interviews, meetings, marriages, etc. are often based on clothing styles. The rise in the fashion industry and its…

eess.AS2020★ 1 cited

Unsupervised Generative Adversarial Alignment Representation for Sheet music, Audio and Lyrics

Donghuo Zeng, Yi Yu, Keizo Oyama

Sheet music, audio, and lyrics are three main modalities during writing a song. In this paper, we propose an unsupervised generative adversarial alignment representation (UGAAR) mo…

cs.CL2020

End-to-end Named Entity Recognition from English Speech

Hemant Yadav, Sreyan Ghosh, Yi Yu +1

Named entity recognition (NER) from text has been a widely studied problem and usually extracts semantic information from text. Until now, NER from speech is mostly studied in a tw…

cs.CV2020★ 5 cited

C3VQG: Category Consistent Cyclic Visual Question Generation

Shagun Uppal, Anish Madan, Sarthak Bhagat +2

Visual Question Generation (VQG) is the task of generating natural questions based on an image. Popular methods in the past have explored image-to-sequence architectures trained wi…

cs.LG2019

Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions

Osaid Rehman Nasir, Shailesh Kumar Jha, Manraj Singh Grover +3

Powerful generative adversarial networks (GAN) have been developed to automatically synthesize realistic images from text. However, most existing tasks are limited to generating si…