Papers by Kejun Liu
TeleMelody: Lyric-to-Melody Generation with a Template-Based Two-Stage Method (2022.emnlp-main)
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Zeqian Ju, Peiling Lu, Xu Tan, Rui Wang, Chen Zhang, Songruoyao Wu, Kejun Zhang, Xiang-Yang Li, Tao Qin, Tie-Yan Liu
| Challenge: | a new lyric-to-melody generation system bridges the gap between lyrics and melodies . previous generation systems lack paired data and lack of control on generated melodie. |
| Approach: | They develop a lyric-to-melody generation system with music template to bridge the gap between lyrics and melodies. |
| Outcome: | The proposed system bridges the gap between lyrics and melodies by using music template. |
Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis (2023.emnlp-main)
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| Challenge: | Multimodal Sentiment Analysis (MSA) is effective when using rich information from multiple sources, but the potential sentiment-irrelevant information across modalities may hinder the performance from being further improved. |
| Approach: | They propose an Adaptive Language-guided Multimodal Transformer (ALMT) that learns an irrelevance/conflict-suppressing representation from visual and audio features under guidance of language features at different scales. |
| Outcome: | The proposed model achieves state-of-the-art on several popular datasets and an abundance of ablation shows the effectiveness of the proposed model. |
Generative Music Models’ Alignment with Professional and Amateur Users’ Expectations (2025.findings-acl)
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| Challenge: | Recent years have witnessed rapid advances in text-to-music generation using large language models. |
| Approach: | They propose a task to align AI-generated music with human expressions . they use a dataset of over 1.5 million songs to analyze their content . |
| Outcome: | The proposed framework outperforms baseline models and facilitates end-to-end generation of songs audio. |