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eess.AS2021
Loss Prediction: End-to-End Active Learning Approach For Speech Recognition
Jian Luo, Jianzong Wang, Ning Cheng +1
End-to-end speech recognition systems usually require huge amounts of labeling resource, while annotating the speech data is complicated and expensive. Active learning is the solut…
eess.AS2021
Dropout Regularization for Self-Supervised Learning of Transformer Encoder Speech Representation
Jian Luo, Jianzong Wang, Ning Cheng +1
Predicting the altered acoustic frames is an effective way of self-supervised learning for speech representation. However, it is challenging to prevent the pretrained model from ov…
eess.AS2021★ 2 cited
Unidirectional Memory-Self-Attention Transducer for Online Speech Recognition
Jian Luo, Jianzong Wang, Ning Cheng +1
Self-attention models have been successfully applied in end-to-end speech recognition systems, which greatly improve the performance of recognition accuracy. However, such attentio…