1 code implementation • 30 Jan 2022 • Minglun Han, Linhao Dong, Zhenlin Liang, Meng Cai, Shiyu Zhou, Zejun Ma, Bo Xu
Nowadays, most methods in end-to-end contextual speech recognition bias the recognition process towards contextual knowledge.
no code implementations • 23 Nov 2018 • Qunbi Zhuge, Xiaobo Zeng, Huazhi Lun, Meng Cai, Xiaomin Liu, Weisheng Hu
In this paper, we present the application of machine learning (ML) in NLI modeling and monitoring.
no code implementations • 3 Nov 2020 • Mingkun Huang, Jun Zhang, Meng Cai, Yang Zhang, Jiali Yao, Yongbin You, Yi He, Zejun Ma
In this work, we analyze the cause of the huge gradient variance in RNN-T training and proposed a new \textit{normalized jointer network} to overcome it.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 3 Nov 2020 • Mingkun Huang, Meng Cai, Jun Zhang, Yang Zhang, Yongbin You, Yi He, Zejun Ma
In this work we propose an inference technique, asynchronous revision, to unify streaming and non-streaming speech recognition models.
no code implementations • 24 Nov 2020 • Xiaomin Liu, Huazhi Lun, Ruoxuan Gao, Meng Cai, Lilin Yi, Weisheng Hu, Qunbi Zhuge
For further improving the capacity and reliability of optical networks, a closed-loop autonomous architecture is preferred.
no code implementations • 8 Oct 2021 • Shaoshi Ling, Chen Shen, Meng Cai, Zejun Ma
In the recent trend of semi-supervised speech recognition, both self-supervised representation learning and pseudo-labeling have shown promising results.
no code implementations • 13 Jul 2023 • Yichen Liu, Xiaomin Liu, Yihao Zhang, Meng Cai, Mengfan Fu, Xueying Zhong, Lilin Yi, Weisheng Hu, Qunbi Zhuge
To enable intelligent and self-driving optical networks, high-accuracy physical layer models are required.