1 code implementation • 14 Feb 2024 • Liwei Lin, Gus Xia, Yixiao Zhang, Junyan Jiang
We apply this method to fine-tune MusicGen, a leading autoregressive music generation model.
1 code implementation • 26 Oct 2023 • Liwei Lin, Gus Xia, Junyan Jiang, Yixiao Zhang
We aim to further equip the models with direct and content-based controls on innate music languages such as pitch, chords and drum track.
no code implementations • Nature 2022 • Ruiqi Guo, Fanping Sui, Wei Yue, Zekai Wang, Sedat Pala, Kunying Li, Renxiao Xu, Liwei Lin
With reasonable training, our deep learning neural network becomes a high-speed, high-accuracy calculator: it can identify the flexural mode frequency and the quality factor 4. 6 × 10 times and 2. 6 × 10 times faster, respectively, than conventional numerical simulation packages, with good accuracies of 98. 8 ± 1. 6% and 96. 8 ± 3. 1%, respectively.
1 code implementation • 7 Aug 2021 • Liwei Lin, Qiuqiang Kong, Junyan Jiang, Gus Xia
We propose a unified model for three inter-related tasks: 1) to \textit{separate} individual sound sources from a mixed music audio, 2) to \textit{transcribe} each sound source to MIDI notes, and 3) to\textit{ synthesize} new pieces based on the timbre of separated sources.
1 code implementation • 11 Sep 2019 • Liwei Lin, Xiangdong Wang, Hong Liu, Yueliang Qian
In this paper, we describe in detail the system we submitted to DCASE2019 task 4: sound event detection (SED) in domestic environments.
1 code implementation • 6 Jun 2019 • Liwei Lin, Xiangdong Wang, Hong Liu, Yueliang Qian
Instead of designing a single model by considering a trade-off between the two sub-targets, we design a teacher model aiming at audio tagging to guide a student model aiming at boundary detection to learn using the unlabeled data.
1 code implementation • 24 May 2019 • Liwei Lin, Xiangdong Wang, Hong Liu, Yueliang Qian
In this paper, a special decision surface for the weakly-supervised sound event detection (SED) and a disentangled feature (DF) for the multi-label problem in polyphonic SED are proposed.
no code implementations • 27 Apr 2019 • Jinkun Cao, Jinhao Zhu, Liwei Lin, Zhengui Xue, Ruhui Ma, Haibing Guan
To avoid privacy leaks, outsourced data usually is encrypted before being sent to cloud servers, which disables traditional search schemes for plain text.