most citedExploiting Negative Preference in Content-based Music Recommendation with Contrastive Learning

21 citations · 23 across the 4 of their papers we have counts for

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cs.SD2024

Removing Speaker Information from Speech Representation using Variable-Length Soft Pooling

Injune Hwang, Kyogu Lee

Recently, there have been efforts to encode the linguistic information of speech using a self-supervised framework for speech synthesis. However, predicting representations from su…

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…

cs.SD2023

Blind Estimation of Audio Processing Graph

Sungho Lee, Jaehyun Park, Seungryeol Paik +1

Musicians and audio engineers sculpt and transform their sounds by connecting multiple processors, forming an audio processing graph. However, most deep-learning methods overlook t…

cs.SD20221 cited

Sketching the Expression: Flexible Rendering of Expressive Piano Performance with Self-Supervised Learning

Seungyeon Rhyu, Sarah Kim, Kyogu Lee

We propose a system for rendering a symbolic piano performance with flexible musical expression. It is necessary to actively control musical expression for creating a new music per…

cs.SD20221 cited

Towards robust music source separation on loud commercial music

Chang-Bin Jeon, Kyogu Lee

Nowadays, commercial music has extreme loudness and heavily compressed dynamic range compared to the past. Yet, in music source separation, these characteristics have not been thor…