no code implementations • COLING 2022 • Xueyuan Chen, Shun Lei, Zhiyong Wu, Dong Xu, Weifeng Zhao, Helen Meng
On top of these, a bi-reference attention mechanism is used to align both local-scale reference style embedding sequence and local-scale context style embedding sequence with corresponding phoneme embedding sequence.
no code implementations • 19 Dec 2023 • Xueyuan Chen, Xi Wang, Shaofei Zhang, Lei He, Zhiyong Wu, Xixin Wu, Helen Meng
Both objective and subjective evaluations demonstrate that our proposed method can effectively improve the naturalness and expressiveness of the synthesized speech in audiobook synthesis especially for the role and out-of-domain scenarios.
1 code implementation • 8 May 2023 • Junran Wu, Xueyuan Chen, Bowen Shi, Shangzhe Li, Ke Xu
In contrastive learning, the choice of ``view'' controls the information that the representation captures and influences the performance of the model.
1 code implementation • 26 Jun 2022 • Junran Wu, Xueyuan Chen, Ke Xu, Shangzhe Li
In addition to SEP, we further design two classification models, SEP-G and SEP-N for graph classification and node classification, respectively.
1 code implementation • 31 Mar 2022 • Xueyuan Chen, Changhe Song, Yixuan Zhou, Zhiyong Wu, Changbin Chen, Zhongqin Wu, Helen Meng
In this paper, we propose a span-based Mandarin prosodic structure prediction model to obtain an optimal prosodic structure tree, which can be converted to corresponding prosodic label sequence.
1 code implementation • 4 Jun 2021 • Junran Wu, Ke Xu, Xueyuan Chen, Shangzhe Li, Jichang Zhao
Then, structural information, referring to associations among temporal points and the node weights, is extracted from the mapped graphs to resolve the problems regarding long-range dependencies and the chaotic property.