6 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…
StereoFoley: Object-Aware Stereo Audio Generation from Video
Tornike Karchkhadze, Kuan-Lin Chen, Mojtaba Heydari +4
We present StereoFoley, a video-to-audio generation framework that produces semantically aligned, temporally synchronized, and spatially accurate stereo sound at 48 kHz. While rece…
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…
Simultaneous Music Separation and Generation Using Multi-Track Latent Diffusion Models
Tornike Karchkhadze, Mohammad Rasool Izadi, Shlomo Dubnov
Diffusion models have recently shown strong potential in both music generation and music source separation tasks. Although in early stages, a trend is emerging towards integrating…
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…
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…