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20232026
most citedSearching For Music Mixing Graphs: A Pruning Approach

1 citations · 1 across the 11 of their papers we have counts for

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cs.SD2024

Variable Bitrate Residual Vector Quantization for Audio Coding

Yunkee Chae, Woosung Choi, Yuhta Takida +8

Recent state-of-the-art neural audio compression models have progressively adopted residual vector quantization (RVQ). Despite this success, these models employ a fixed number of c…

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

Wavespace: A Highly Explorable Wavetable Generator

Hazounne Lee, Kihong Kim, Sungho Lee +1

Wavetable synthesis generates quasi-periodic waveforms of musical tones by interpolating a list of waveforms called wavetable. As generative models that utilize latent representati…

cs.SD2024★ 1 cited

Searching For Music Mixing Graphs: A Pruning Approach

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

Music mixing is compositional -- experts combine multiple audio processors to achieve a cohesive mix from dry source tracks. We propose a method to reverse engineer this process fr…

cs.SD2024

Music Auto-Tagging with Robust Music Representation Learned via Domain Adversarial Training

Haesun Joung, Kyogu Lee

Music auto-tagging is crucial for enhancing music discovery and recommendation. Existing models in Music Information Retrieval (MIR) struggle with real-world noise such as environm…

eess.AS2024

DDD: A Perceptually Superior Low-Response-Time DNN-based Declipper

Jayeon Yi, Junghyun Koo, Kyogu Lee

Clipping is a common nonlinear distortion that occurs whenever the input or output of an audio system exceeds the supported range. This phenomenon undermines not only the perceptio…