activity
20182026
most citedExpressive Neural Voice Cloning

18 citations · 80 across the 22 of their papers we have counts for

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28 papers · 1 filter

cs.SD2026

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…

cs.SD2025

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…

cs.SD2025

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…

cs.SD2024

Interpreting Graphic Notation with MusicLDM: An AI Improvisation of Cornelius Cardew's Treatise

Tornike Karchkhadze, Keren Shao, Shlomo Dubnov

This work presents a novel method for composing and improvising music inspired by Cornelius Cardew's Treatise, using AI to bridge graphic notation and musical expression. By levera…

cs.SD2024

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…

cs.SD2024

Multi-Track MusicLDM: Towards Versatile Music Generation with Latent Diffusion Model

Tornike Karchkhadze, Mohammad Rasool Izadi, Ke Chen +2

Diffusion models have shown promising results in cross-modal generation tasks involving audio and music, such as text-to-sound and text-to-music generation. These text-controlled m…