24 citations · 50 across the 23 of their papers we have counts for
22 papers · 1 filter
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…
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…
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…
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…
Fast Text-to-Audio Generation with Adversarial Post-Training
Zachary Novack, Zach Evans, Zack Zukowski +8
Text-to-audio systems, while increasingly performant, are slow at inference time, thus making their latency unpractical for many creative applications. We present Adversarial Relat…
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…