Shih-Lun Wu
Orcid: 0009-0001-9653-006X
According to our database1,
Shih-Lun Wu
authored at least 18 papers
between 2020 and 2024.
Collaborative distances:
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Bibliography
2024
IEEE ACM Trans. Audio Speech Lang. Process., 2024
Audio Prompt Adapter: Unleashing Music Editing Abilities for Text-to-Music with Lightweight Finetuning.
CoRR, 2024
Improving Audio Captioning Models with Fine-Grained Audio Features, Text Embedding Supervision, and LLM Mix-Up Augmentation.
Proceedings of the IEEE International Conference on Acoustics, 2024
2023
ACM Trans. Cyber Phys. Syst., July, 2023
IEEE Trans. Multim., 2023
MuseMorphose: Full-Song and Fine-Grained Piano Music Style Transfer With One Transformer VAE.
IEEE ACM Trans. Audio Speech Lang. Process., 2023
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023
Compose & Embellish: Well-Structured Piano Performance Generation via A Two-Stage Approach.
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
The Pipeline System of ASR and NLU with MLM-based data Augmentation Toward Stop Low-Resource Challenge.
Proceedings of the IEEE International Conference on Acoustics, 2023
A Study on the Integration of Pipeline and E2E SLU Systems for Spoken Semantic Parsing Toward Stop Quality Challenge.
Proceedings of the IEEE International Conference on Acoustics, 2023
Listener Model for the PhotoBook Referential Game with CLIPScores as Implicit Reference Chain.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023
2021
MuseMorphose: Full-Song and Fine-Grained Music Style Transfer with Just One Transformer VAE.
CoRR, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Efficient System Verification with Multiple Weakly-Hard Constraints for Runtime Monitoring.
Proceedings of the Runtime Verification - 20th International Conference, 2020
The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-composed Music through Quantitative Measures.
Proceedings of the 21th International Society for Music Information Retrieval Conference, 2020
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020