今年入选 ICASSP 2023 的论文中,说话人识别(声纹识别)方向约有64篇,初步划分为Speaker Verification(31篇)、Speaker Recognition(9篇)、Speaker Diarization(17篇)、Anti-Spoofing(4篇)、others(3篇)五种类型。 本文是 ICASSP 2023说话人识别方向论文合集系列第一期,整理了Speaker Verification(前15篇)部分的论文简述...
本文是 ICASSP 2023说话人识别方向论文合集系列第二期,整理了 Speaker Verification 后16篇和 Speaker Diarization 部分的17篇。 1 Speaker Verification 16.Margin-Mixup: A Method For Robust Speaker Verification In Multi-Speaker Audio 标题:边缘混合:一种多说话人音频中的鲁棒性说话人验证方法...
现任中山大学教授)、吴刚(教授,工业自动化研究所所长) 、印卧涛(UCLA 教授,晨兴应用数学金奖得主)在 2014 年合著的《On the Linear Convergence of the ADMM in Decentralized Consensus Optimization》获得 Young Author Best Paper Award(青年作者最佳论文奖)。
If you find this repo useful for your research, please consider citing our paper: @article{jang2023recycleanddistill, title={Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation}, author={Kangwook Jang and Sung...
{2023} } @article{mei2023wavcaps, title={WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research}, author={Mei, Xinhao and Meng, Chutong and Liu, Haohe and Kong, Qiuqiang and Ko, Tom and Zhao, Chengqi and Plumbley, Mark D and Zou, ...
Deep Speech Enhancement Challenge is the 5th edition of deep noise suppression (DNS) challenges organized at ICASSP 2023 Signal Processing Grand Challenges. DNS challenges were organized during 2019-2023 to stimulate research in deep speech enhancement (DSE). Previous DNS challenges were organized at ...
ICASSP 2024 Grand Challenge Paper Submission and Judging Period: December 17, 2023 – 11:59 PM PT January 2, 2024. To submit a paper, visitMicrosoft Conference Management Toolkit(opens in new tab)(opens in new tab). The entry limit is one per person during the Entry Period. Any...
Today, according to the Cisco Annual Internet Report (2018-2023), thefastest-growing category of Internet traffic is machine-to-machinecommunication. In particular, machine-to-machine communication of images andvideos represents a new challenge and opens up new perspectives in the contextof data comp...
其中来自中国科学技术大学的施伟(博士生)、袁坤(研究生)凭借与凌青(时任副教授,现任中山大学教授)、吴刚(教授,工业自动化研究所所长) 、印卧涛(UCLA 教授,晨兴应用数学金奖得主)在 2014 年合著的《On the Linear Convergence of the ADMM in Decentralized Consensus Optimization》获得 Young Author Best Paper Award...
Most models submitted to challenge were personalized models, same team is winner in both tracks where the best models has improvement of 0.145 and 0.141 in challenge's Score as compared to noisy blind testset. 展开 DOI: 10.48550/arXiv.2303.11510 年份: 2023 ...