2 code implementations • 14 Aug 2023 • Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai, Woosung Choi, Marco Martínez-Ramírez, WeiHsiang Liao, Igor Gadelha, Geraldo Ramos, Eddie Hsu, Hugo Rodrigues, Fabian-Robert Stöter, Alexandre Défossez, Yi Luo, Jianwei Yu, Dipam Chakraborty, Sharada Mohanty, Roman Solovyev, Alexander Stempkovskiy, Tatiana Habruseva, Nabarun Goswami, Tatsuya Harada, Minseok Kim, Jun Hyung Lee, Yuanliang Dong, Xinran Zhang, Jiafeng Liu, Yuki Mitsufuji
We propose a formalization of the errors that can occur in the design of a training dataset for MSS systems and introduce two new datasets that simulate such errors: SDXDB23_LabelNoise and SDXDB23_Bleeding.
1 code implementation • 10 May 2022 • Jiafeng Liu, Yuanliang Dong, Zehua Cheng, Xinran Zhang, Xiaobing Li, Feng Yu, Maosong Sun
In this work, we propose a permutation invariant language model, SymphonyNet, as a solution for symbolic symphony music generation.
Ranked #1 on Audio Generation on Symphony music
1 code implementation • 9 Dec 2021 • Haohe Liu, Qiuqiang Kong, Jiafeng Liu
On the MUSDB18HQ test set, we propose a 276-layer CWS-PResUNet and achieve state-of-the-art (SoTA) performance on vocals with an 8. 92 signal-to-distortion ratio (SDR) score.
Ranked #11 on Music Source Separation on MUSDB18-HQ
no code implementations • 27 Aug 2021 • Xinran Zhang, Maosong Sun, Jiafeng Liu, Xiaobing Li
We propose nucleus sampling with randomized head (NS-RH) algorithm, which randomizes the high frequency part ("head") of the predicted distribution, in order to emphasize on the "comparatively low frequency" words.
no code implementations • 13 Mar 2021 • Xinran Zhang, Maosong Sun, Jiafeng Liu, Xiaobing Li
In natural language processing (NLP), the semantic similarity task requires large-scale, high-quality human-annotated labels for fine-tuning or evaluation.
no code implementations • 13 Mar 2021 • Xinran Zhang, Maosong Sun, Jiafeng Liu, Xiaobing Li
Traditional stochastic sampling methods only focus on truncating the unreliable "tail" of the distribution, and do not address the "head" part, which we show might contain tedious or even repetitive candidates with high probability that lead to repetition loops.