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20222026
most citedThe Sound Demixing Challenge 2023 $\unicode{x2013}$ Music Demixing Track

26 citations · 39 across the 13 of their papers we have counts for

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10 papers · 1 filter

cs.SD2026

Agentic Music Post-Production

Jaywon Koo, Junghyun Koo, Marco A. Martinez-Ramirez +5

We introduce MixAgent, an agentic pipeline for music post-production that follows the workflow of audio engineers to build interpretable and editable mixing plans guided by a refer…

cs.SD2026

Exploring the Design Space of Representation Learning for Audio Transformations

Sungho Lee, Marco Martínez-Ramírez, Junghyun Koo +3

Neural audio representation learning has enabled a range of content-oriented applications, but the resulting features remain limited for tasks involving audio processing. Furthermo…

cs.SD2026

LLM2Fx-Tools: Tool Calling For Music Post-Production

Seungheon Doh, Junghyun Koo, Marco A. Martínez-Ramírez +5

This paper introduces LLM2Fx-Tools, a multimodal tool-calling framework that generates executable sequences of audio effects (Fx-chain) for music post-production. LLM2Fx-Tools uses…

cs.SD2025

Fx-Encoder++: Extracting Instrument-Wise Audio Effects Representations from Mixtures

Yen-Tung Yeh, Junghyun Koo, Marco A. Martínez-Ramírez +3

General-purpose audio representations have proven effective across diverse music information retrieval applications, yet their utility in intelligent music production remains limit…

cs.SD2025

Can Large Language Models Predict Audio Effects Parameters from Natural Language?

Seungheon Doh, Junghyun Koo, Marco A. Martínez-Ramírez +3

In music production, manipulating audio effects (Fx) parameters through natural language has the potential to reduce technical barriers for non-experts. We present LLM2Fx, a framew…

cs.SD2025

Improving Inference-Time Optimisation for Vocal Effects Style Transfer with a Gaussian Prior

Chin-Yun Yu, Marco A. Martínez-Ramírez, Junghyun Koo +3

Style Transfer with Inference-Time Optimisation (ST-ITO) is a recent approach for transferring the applied effects of a reference audio to an audio track. It optimises the effect p…

cs.SD2025

DiffVox: A Differentiable Model for Capturing and Analysing Vocal Effects Distributions

Chin-Yun Yu, Marco A. Martínez-Ramírez, Junghyun Koo +4

This study introduces a novel and interpretable model, DiffVox, for matching vocal effects in music production. DiffVox, short for ``Differentiable Vocal Fx", integrates parametric…

cs.SD2024

Latent Diffusion Bridges for Unsupervised Musical Audio Timbre Transfer

Michele Mancusi, Yurii Halychanskyi, Kin Wai Cheuk +8

Music timbre transfer is a challenging task that involves modifying the timbral characteristics of an audio signal while preserving its melodic structure. In this paper, we propose…

cs.SD2024

GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch

Sungho Lee, Marco Martínez-Ramírez, Wei-Hsiang Liao +4

We present GRAFX, an open-source library designed for handling audio processing graphs in PyTorch. Along with various library functionalities, we describe technical details on the…

cs.SD2024

Improving Unsupervised Clean-to-Rendered Guitar Tone Transformation Using GANs and Integrated Unaligned Clean Data

Yu-Hua Chen, Woosung Choi, Wei-Hsiang Liao +5

Recent years have seen increasing interest in applying deep learning methods to the modeling of guitar amplifiers or effect pedals. Existing methods are mainly based on the supervi…