2 citations · 5 across the 8 of their papers we have counts for
8 papers
Speech Augmentation Based Unsupervised Learning for Keyword Spotting
Jian Luo, Jianzong Wang, Ning Cheng +2
In this paper, we investigated a speech augmentation based unsupervised learning approach for keyword spotting (KWS) task. KWS is a useful speech application, yet also heavily depe…
Adaptive Activation Network For Low Resource Multilingual Speech Recognition
Jian Luo, Jianzong Wang, Ning Cheng +2
Low resource automatic speech recognition (ASR) is a useful but thorny task, since deep learning ASR models usually need huge amounts of training data. The existing models mostly e…
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…
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…
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…
Multi-QuartzNet: Multi-Resolution Convolution for Speech Recognition with Multi-Layer Feature Fusion
Jian Luo, Jianzong Wang, Ning Cheng +2
In this paper, we propose an end-to-end speech recognition network based on Nvidia's previous QuartzNet model. We try to promote the model performance, and design three components:…