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Exploiting Semi-Supervised Training Through a Dropout Regularization in End-to-End Speech Recognition

机译：通过端到端语音识别中的辍学正常化利用半监督培训

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Subhadeep Dey; Petr Motlicek; Trung Bui; Franck Dernoncourt;
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年度 2019
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1. Regularized Urdu Speech Recognition with Semi-Supervised Deep Learning [J] . Mohammad Ali Humayun, Ibrahim A. Hameed, Syed Muslim Shah, Applied Sciences . 2019,第9期

机译：具有半监督深度学习的正则化乌尔都语语音识别
2. Adversarial Regularization for Attention Based End-to-End Robust Speech Recognition [J] . Su Sining, Guo Pengcheng, Xie Lei, Audio, Speech, and Language Processing, IEEE/ACM Transactions on . 2019,第11期

机译：基于注意力的端到端鲁棒语音识别的对抗规则化
3. End-to-End Multilingual Speech Recognition System with Language Supervision Training [J] . Danyang LIU, Ji XU, Pengyuan ZHANG IEICE transactions on information and systems . 2020,第6期

机译：具有语言监督培训的端到端多语言语音识别系统
4. Robust Audio-visual Speech Recognition Using Bimodal Dfsmn with Multi-condition Training and Dropout Regularization [C] . Shiliang Zhang, Ming Lei, Bin Ma, IEEE International Conference on Acoustics, Speech and Signal Processing . 2019

机译：结合多条件训练和辍学正则化的双峰Dfsmn进行稳健的视听语音识别
5. Semi-Supervised Training for Automatic Speech Recognition [D] . Manohar, Vimal. 2019

机译：半监督自动演讲识别培训
6. Dynamic Acoustic Unit Augmentation with BPE-Dropout for Low-Resource End-to-End Speech Recognition [O] . Aleksandr Laptev, Andrei Andrusenko, Ivan Podluzhny, 2021

机译：用BPE-ropout进行动态声学单元增强用于低资源端到端语音识别
7. Semi-supervised domain adaptation using unlabeled data for end-to-end speech recognition [O] . Hyeonjae Jeong, Jahyun Goo, Hoirin Kim 2020

机译：半监控域适应使用未标记数据进行端到端语音识别

Exploiting Semi-Supervised Training Through a Dropout Regularization in End-to-End Speech Recognition

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