21 citations · 68 across the 16 of their papers we have counts for
16 papers
Temporal Adaptation of Pre-trained Foundation Models for Music Structure Analysis
Yixiao Zhang, Haonan Chen, Ju-Chiang Wang +1
Audio-based music structure analysis (MSA) is an essential task in Music Information Retrieval that remains challenging due to the complexity and variability of musical form. Recen…
Improving Controllability and Editability for Pretrained Text-to-Music Generation Models
Yixiao Zhang
The field of AI-assisted music creation has made significant strides, yet existing systems often struggle to meet the demands of iterative and nuanced music production. These chall…
The Interpretation Gap in Text-to-Music Generation Models
Yongyi Zang, Yixiao Zhang
Large-scale text-to-music generation models have significantly enhanced music creation capabilities, offering unprecedented creative freedom. However, their ability to collaborate…
Instruct-MusicGen: Unlocking Text-to-Music Editing for Music Language Models via Instruction Tuning
Yixiao Zhang, Yukara Ikemiya, Woosung Choi +7
Recent advances in text-to-music editing, which employ text queries to modify music (e.g.\ by changing its style or adjusting instrumental components), present unique challenges an…
Arrange, Inpaint, and Refine: Steerable Long-term Music Audio Generation and Editing via Content-based Controls
Liwei Lin, Gus Xia, Yixiao Zhang +1
Controllable music generation plays a vital role in human-AI music co-creation. While Large Language Models (LLMs) have shown promise in generating high-quality music, their focus…
MusicMagus: Zero-Shot Text-to-Music Editing via Diffusion Models
Yixiao Zhang, Yukara Ikemiya, Gus Xia +5
Recent advances in text-to-music generation models have opened new avenues in musical creativity. However, music generation usually involves iterative refinements, and how to edit…
The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation
Ilaria Manco, Benno Weck, SeungHeon Doh +10
We introduce the Song Describer dataset (SDD), a new crowdsourced corpus of high-quality audio-caption pairs, designed for the evaluation of music-and-language models. The dataset…
Content-based Controls For Music Large Language Modeling
Liwei Lin, Gus Xia, Junyan Jiang +1
Recent years have witnessed a rapid growth of large-scale language models in the domain of music audio. Such models enable end-to-end generation of higher-quality music, and some a…
Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing
Yixiao Zhang, Akira Maezawa, Gus Xia +2
Creating music is iterative, requiring varied methods at each stage. However, existing AI music systems fall short in orchestrating multiple subsystems for diverse needs. To addres…
AI (r)evolution -- where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning
Giovanni Bindi, Nils Demerlé, Rodrigo Diaz +18
Artificial Intelligence (AI) technologies such as deep learning are evolving very quickly bringing many changes to our everyday lives. To explore the future impact and potential of…
Exploring XAI for the Arts: Explaining Latent Space in Generative Music
Nick Bryan-Kinns, Berker Banar, Corey Ford +4
Explainable AI has the potential to support more interactive and fluid co-creative AI systems which can creatively collaborate with people. To do this, creative AI models need to b…
Vis2Mus: Exploring Multimodal Representation Mapping for Controllable Music Generation
Runbang Zhang, Yixiao Zhang, Kai Shao +2
In this study, we explore the representation mapping from the domain of visual arts to the domain of music, with which we can use visual arts as an effective handle to control musi…
Learning Hierarchical Metrical Structure Beyond Measures
Junyan Jiang, Daniel Chin, Yixiao Zhang +1
Music contains hierarchical structures beyond beats and measures. While hierarchical structure annotations are helpful for music information retrieval and computer musicology, such…
Interpreting Song Lyrics with an Audio-Informed Pre-trained Language Model
Yixiao Zhang, Junyan Jiang, Gus Xia +1
Lyric interpretations can help people understand songs and their lyrics quickly, and can also make it easier to manage, retrieve and discover songs efficiently from the growing mas…
Learning Interpretable Representation for Controllable Polyphonic Music Generation
Ziyu Wang, Dingsu Wang, Yixiao Zhang +1
While deep generative models have become the leading methods for algorithmic composition, it remains a challenging problem to control the generation process because the latent vari…
PIANOTREE VAE: Structured Representation Learning for Polyphonic Music
Ziyu Wang, Yiyi Zhang, Yixiao Zhang +4
The dominant approach for music representation learning involves the deep unsupervised model family variational autoencoder (VAE). However, most, if not all, viable attempts on thi…