38 citations · 75 across the 16 of their papers we have counts for
16 papers
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…
Listener Model for the PhotoBook Referential Game with CLIPScores as Implicit Reference Chain
Shih-Lun Wu, Yi-Hui Chou, Liangze Li
PhotoBook is a collaborative dialogue game where two players receive private, partially-overlapping sets of images and resolve which images they have in common. It presents machine…
Tensor decomposition for minimization of E2E SLU model toward on-device processing
Yosuke Kashiwagi, Siddhant Arora, Hayato Futami +6
Spoken Language Understanding (SLU) is a critical speech recognition application and is often deployed on edge devices. Consequently, on-device processing plays a significant role…
The Pipeline System of ASR and NLU with MLM-based Data Augmentation toward STOP Low-resource Challenge
Hayato Futami, Jessica Huynh, Siddhant Arora +6
This paper describes our system for the low-resource domain adaptation track (Track 3) in Spoken Language Understanding Grand Challenge, which is a part of ICASSP Signal Processing…
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge
Siddhant Arora, Hayato Futami, Shih-Lun Wu +6
Recently there have been efforts to introduce new benchmark tasks for spoken language understanding (SLU), like semantic parsing. In this paper, we describe our proposed spoken sem…
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…
Relative Positional Encoding for Transformers with Linear Complexity
Antoine Liutkus, Ondřej Cífka, Shih-Lun Wu +3
Recent advances in Transformer models allow for unprecedented sequence lengths, due to linear space and time complexity. In the meantime, relative positional encoding (RPE) was pro…
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…
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights
Shih-Lun Wu, Hsiao-Yen Tung, Yu-Lun Hsu
The quality grading of mangoes is a crucial task for mango growers as it vastly affects their profit. However, until today, this process still relies on laborious efforts of humans…
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…