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Live Music Diffusion Models: Efficient Fine-Tuning and Post-Training of Interactive Diffusion Music Generators
Zachary Novack, Stephen Brade, Haven Kim +8
Interactive streaming music generation promises the use of generative models for live performance and co-creation that is impossible with offline models. However, SOTA models exist…
BACHI: Boundary-Aware Symbolic Chord Recognition Through Masked Iterative Decoding on Pop and Classical Music
Mingyang Yao, Ke Chen, Shlomo Dubnov +1
Automatic chord recognition (ACR) via deep learning models has gradually achieved promising recognition accuracy, yet two key challenges remain. First, prior work has primarily foc…
MuseTok: Symbolic Music Tokenization for Generation and Semantic Understanding
Jingyue Huang, Zachary Novack, Phillip Long +4
Discrete representation learning has shown promising results across various domains, including generation and understanding in image, speech and language. Inspired by these advance…
WildFX: A DAW-Powered Pipeline for In-the-Wild Audio FX Graph Modeling
Qihui Yang, Taylor Berg-Kirkpatrick, Julian McAuley +1
Despite rapid progress in end-to-end AI music generation, AI-driven modeling of professional Digital Signal Processing (DSP) workflows remains challenging. In particular, while the…
Generating Symbolic Music from Natural Language Prompts using an LLM-Enhanced Dataset
Weihan Xu, Julian McAuley, Taylor Berg-Kirkpatrick +2
Recent years have seen many audio-domain text-to-music generation models that rely on large amounts of text-audio pairs for training. However, symbolic-domain controllable music ge…
Are you really listening? Boosting Perceptual Awareness in Music-QA Benchmarks
Yongyi Zang, Sean O'Brien, Taylor Berg-Kirkpatrick +2
Large Audio Language Models (LALMs), where pretrained text LLMs are finetuned with audio input, have made remarkable progress in music understanding. However, current evaluation me…