10 papers
Improving Music Source Separation with Diffusion and Consistency Refinement
Tornike Karchkhadze, Mohammad Rasool Izadi, Shuo Zhang +1
In this work, we propose an approach to music source separation that uses a generative diffusion model as a last-stage refinement on top of a deterministic separator, progressively…
Towards Real-Time Human-AI Musical Co-Performance: Accompaniment Generation with Latent Diffusion Models and MAX/MSP
Tornike Karchkhadze, Shlomo Dubnov
We present a framework for real-time human-AI musical co-performance, in which a latent diffusion model generates instrumental accompaniment in response to a live stream of context…
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…
Synthesizing Composite Hierarchical Structure from Symbolic Music Corpora
Ilana Shapiro, Ruanqianqian Huang, Zachary Novack +5
Western music is an innately hierarchical system of interacting levels of structure, from fine-grained melody to high-level form. In order to analyze music compositions holisticall…
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…
kNN-SVC: Robust Zero-Shot Singing Voice Conversion with Additive Synthesis and Concatenation Smoothness Optimization
Keren Shao, Ke Chen, Matthew Baas +1
Robustness is critical in zero-shot singing voice conversion (SVC). This paper introduces two novel methods to strengthen the robustness of the kNN-VC framework for SVC. First, kNN…