7 papers
LLM2Fx-Tools: Tool Calling For Music Post-Production
Seungheon Doh, Junghyun Koo, Marco A. MartÃnez-RamÃrez +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…
Automatic Music Mixing using a Generative Model of Effect Embeddings
Eloi Moliner, Marco A. MartÃnez-RamÃrez, Junghyun Koo +5
Music mixing involves combining individual tracks into a cohesive mixture, a task characterized by subjectivity where multiple valid solutions exist for the same input. Existing au…
Improving Inference-Time Optimisation for Vocal Effects Style Transfer with a Gaussian Prior
Chin-Yun Yu, Marco A. MartÃnez-RamÃrez, 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…
DiffVox: A Differentiable Model for Capturing and Analysing Vocal Effects Distributions
Chin-Yun Yu, Marco A. MartÃnez-RamÃrez, 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…
Can Large Language Models Predict Audio Effects Parameters from Natural Language?
Seungheon Doh, Junghyun Koo, Marco A. MartÃnez-RamÃrez +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…
Fx-Encoder++: Extracting Instrument-Wise Audio Effects Representations from Mixtures
Yen-Tung Yeh, Junghyun Koo, Marco A. MartÃnez-RamÃrez +3
General-purpose audio representations have proven effective across diverse music information retrieval applications, yet their utility in intelligent music production remains limit…