6 citations · 10 across the 6 of their papers we have counts for
6 papers
OTF: Optimal Transport based Fusion of Supervised and Self-Supervised Learning Models for Automatic Speech Recognition
Li Fu, Siqi Li, Qingtao Li +6
Self-Supervised Learning (SSL) Automatic Speech Recognition (ASR) models have shown great promise over Supervised Learning (SL) ones in low-resource settings. However, the advantag…
UFO2: A unified pre-training framework for online and offline speech recognition
Li Fu, Siqi Li, Qingtao Li +5
In this paper, we propose a Unified pre-training Framework for Online and Offline (UFO2) Automatic Speech Recognition (ASR), which 1) simplifies the two separate training workflows…
SCaLa: Supervised Contrastive Learning for End-to-End Speech Recognition
Li Fu, Xiaoxiao Li, Runyu Wang +5
End-to-end Automatic Speech Recognition (ASR) models are usually trained to optimize the loss of the whole token sequence, while neglecting explicit phonemic-granularity supervisio…
Incremental Learning for End-to-End Automatic Speech Recognition
Li Fu, Xiaoxiao Li, Libo Zi +4
In this paper, we propose an incremental learning method for end-to-end Automatic Speech Recognition (ASR) which enables an ASR system to perform well on new tasks while maintainin…
Research on Modeling Units of Transformer Transducer for Mandarin Speech Recognition
Li Fu, Xiaoxiao Li, Libo Zi
Modeling unit and model architecture are two key factors of Recurrent Neural Network Transducer (RNN-T) in end-to-end speech recognition. To improve the performance of RNN-T for Ma…
Learning Enhanced Resolution-wise features for Human Pose Estimation
Kun Zhang, Peng He, Ping Yao +6
Recently, multi-resolution networks (such as Hourglass, CPN, HRNet, etc.) have achieved significant performance on pose estimation by combining feature maps of various resolutions.…