18 citations · 42 across the 36 of their papers we have counts for
17 papers · 1 filter
OpenMU: Your Swiss Army Knife for Music Understanding
Mengjie Zhao, Zhi Zhong, Zhuoyuan Mao +5
We present OpenMU-Bench, a large-scale benchmark suite for addressing the data scarcity issue in training multimodal language models to understand music. To construct OpenMU-Bench,…
Music Foundation Model as Generic Booster for Music Downstream Tasks
WeiHsiang Liao, Yuhta Takida, Yukara Ikemiya +13
We demonstrate the efficacy of using intermediate representations from a single foundation model to enhance various music downstream tasks. We introduce SoniDo, a music foundation…
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…
HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning
Ayano Hiranaka, Shang-Fu Chen, Chieh-Hsin Lai +6
Controllable generation through Stable Diffusion (SD) fine-tuning aims to improve fidelity, safety, and alignment with human guidance. Existing reinforcement learning from human fe…
LOCKEY: A Novel Approach to Model Authentication and Deepfake Tracking
Mayank Kumar Singh, Naoya Takahashi, Wei-Hsiang Liao +1
This paper presents a novel approach to deter unauthorized deepfakes and enable user tracking in generative models, even when the user has full access to the model parameters, by i…
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…
DisMix: Disentangling Mixtures of Musical Instruments for Source-level Pitch and Timbre Manipulation
Yin-Jyun Luo, Kin Wai Cheuk, Woosung Choi +8
Existing work on pitch and timbre disentanglement has been mostly focused on single-instrument music audio, excluding the cases where multiple instruments are presented. To fill th…
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…
Towards Assessing Data Replication in Music Generation with Music Similarity Metrics on Raw Audio
Roser Batlle-Roca, Wei-Hsiang Liao, Xavier Serra +2
Recent advancements in music generation are raising multiple concerns about the implications of AI in creative music processes, current business models and impacts related to intel…
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…
SilentCipher: Deep Audio Watermarking
Mayank Kumar Singh, Naoya Takahashi, Weihsiang Liao +1
In the realm of audio watermarking, it is challenging to simultaneously encode imperceptible messages while enhancing the message capacity and robustness. Although recent advanceme…
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…
Instruct-MusicGen: Unlocking Text-to-Music Editing for Music Language Models via Instruction Tuning
Yixiao Zhang, Yukara Ikemiya, Woosung Choi +7
Recent advances in text-to-music editing, which employ text queries to modify music (e.g.\ by changing its style or adjusting instrumental components), present unique challenges an…
PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher
Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao +5
The diffusion model performs remarkable in generating high-dimensional content but is computationally intensive, especially during training. We propose Progressive Growing of Diffu…
MR-MT3: Memory Retaining Multi-Track Music Transcription to Mitigate Instrument Leakage
Hao Hao Tan, Kin Wai Cheuk, Taemin Cho +2
This paper presents enhancements to the MT3 model, a state-of-the-art (SOTA) token-based multi-instrument automatic music transcription (AMT) model. Despite SOTA performance, MT3 h…
MusicMagus: Zero-Shot Text-to-Music Editing via Diffusion Models
Yixiao Zhang, Yukara Ikemiya, Gus Xia +5
Recent advances in text-to-music generation models have opened new avenues in musical creativity. However, music generation usually involves iterative refinements, and how to edit…
HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes
Yuhta Takida, Yukara Ikemiya, Takashi Shibuya +8
Vector quantization (VQ) is a technique to deterministically learn features with discrete codebook representations. It is commonly performed with a variational autoencoding model,…