38 citations · 75 across the 16 of their papers we have counts for
10 papers · 1 filter
MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
Fang-Duo Tsai, Shih-Lun Wu, Weijaw Lee +4
We propose MuseControlLite, a lightweight mechanism designed to fine-tune text-to-music generation models for precise conditioning using various time-varying musical attributes and…
Hookpad Aria: A Copilot for Songwriters
Chris Donahue, Shih-Lun Wu, Yewon Kim +3
We present Hookpad Aria, a generative AI system designed to assist musicians in writing Western pop songs. Our system is seamlessly integrated into Hookpad, a web-based editor desi…
Foundation Models for Music: A Survey
Yinghao Ma, Anders Øland, Anton Ragni +39
In recent years, foundation models (FMs) such as large language models (LLMs) and latent diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This com…
Audio Prompt Adapter: Unleashing Music Editing Abilities for Text-to-Music with Lightweight Finetuning
Fang-Duo Tsai, Shih-Lun Wu, Haven Kim +3
Text-to-music models allow users to generate nearly realistic musical audio with textual commands. However, editing music audios remains challenging due to the conflicting desidera…
Music ControlNet: Multiple Time-varying Controls for Music Generation
Shih-Lun Wu, Chris Donahue, Shinji Watanabe +1
Text-to-music generation models are now capable of generating high-quality music audio in broad styles. However, text control is primarily suitable for the manipulation of global m…
Improving Audio Captioning Models with Fine-grained Audio Features, Text Embedding Supervision, and LLM Mix-up Augmentation
Shih-Lun Wu, Xuankai Chang, Gordon Wichern +4
Automated audio captioning (AAC) aims to generate informative descriptions for various sounds from nature and/or human activities. In recent years, AAC has quickly attracted resear…
Compose & Embellish: Well-Structured Piano Performance Generation via A Two-Stage Approach
Shih-Lun Wu, Yi-Hsuan Yang
Even with strong sequence models like Transformers, generating expressive piano performances with long-range musical structures remains challenging. Meanwhile, methods to compose w…
Theme Transformer: Symbolic Music Generation with Theme-Conditioned Transformer
Yi-Jen Shih, Shih-Lun Wu, Frank Zalkow +2
Attention-based Transformer models have been increasingly employed for automatic music generation. To condition the generation process of such a model with a user-specified sequenc…
MuseMorphose: Full-Song and Fine-Grained Piano Music Style Transfer with One Transformer VAE
Shih-Lun Wu, Yi-Hsuan Yang
Transformers and variational autoencoders (VAE) have been extensively employed for symbolic (e.g., MIDI) domain music generation. While the former boast an impressive capability in…
The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-composed Music through Quantitative Measures
Shih-Lun Wu, Yi-Hsuan Yang
This paper presents the Jazz Transformer, a generative model that utilizes a neural sequence model called the Transformer-XL for modeling lead sheets of Jazz music. Moreover, the m…