10 citations · 36 across the 8 of their papers we have counts for
13 papers
A Sequence-to-Set Network for Nested Named Entity Recognition
Zeqi Tan, Yongliang Shen, Shuai Zhang +2
Named entity recognition (NER) is a widely studied task in natural language processing. Recently, a growing number of studies have focused on the nested NER. The span-based methods…
Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition
Yongliang Shen, Xinyin Ma, Zeqi Tan +3
Named entity recognition (NER) is a well-studied task in natural language processing. Traditional NER research only deals with flat entities and ignores nested entities. The span-b…
FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization
Zhengkun Tian, Jiangyan Yi, Ye Bai +3
Transducer-based models, such as RNN-Transducer and transformer-transducer, have achieved great success in speech recognition. A typical transducer model decodes the output sequenc…
Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERT
Ye Bai, Jiangyan Yi, Jianhua Tao +3
Attention-based encoder-decoder (AED) models have achieved promising performance in speech recognition. However, because the decoder predicts text tokens (such as characters or wor…
Decoupling Pronunciation and Language for End-to-end Code-switching Automatic Speech Recognition
Shuai Zhang, Jiangyan Yi, Zhengkun Tian +3
Despite the recent significant advances witnessed in end-to-end (E2E) ASR system for code-switching, hunger for audio-text paired data limits the further improvement of the models'…
One In A Hundred: Select The Best Predicted Sequence from Numerous Candidates for Streaming Speech Recognition
Zhengkun Tian, Jiangyan Yi, Ye Bai +3
The RNN-Transducers and improved attention-based encoder-decoder models are widely applied to streaming speech recognition. Compared with these two end-to-end models, the CTC model…