6 papers · 1 filter
Spatio-Temporal Audio Language Modeling for Dynamic Sound Sources
Oh Hyun-Bin, Kazuki Shimada, Yuhta Takida +6
Sound events are entities with semantic identities, locations, and trajectories, but current audio-language models usually reason about clips as global event content. Conversely, s…
Large-Scale Training Data Attribution for Music Generative Models via Unlearning
Woosung Choi, Junghyun Koo, Kin Wai Cheuk +7
This paper explores the use of unlearning methods for training data attribution (TDA) in music generative models trained on large-scale datasets. TDA aims to identify which specifi…
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…
SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound Generation
Koichi Saito, Dongjun Kim, Takashi Shibuya +4
Sound content creation, essential for multimedia works such as video games and films, often involves extensive trial-and-error, enabling creators to semantically reflect their arti…
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…