578 citations · 1.3k across the 35 of their papers we have counts for
17 papers · 1 filter
A Survey on Low-Resource Neural Machine Translation
Rui Wang, Xu Tan, Renqian Luo +2
Neural approaches have achieved state-of-the-art accuracy on machine translation but suffer from the high cost of collecting large scale parallel data. Thus, a lot of research has…
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search
Jin Xu, Xu Tan, Renqian Luo +4
While pre-trained language models (e.g., BERT) have achieved impressive results on different natural language processing tasks, they have large numbers of parameters and suffer fro…
MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition
Linghui Meng, Jin Xu, Xu Tan +3
In this paper, we propose MixSpeech, a simple yet effective data augmentation method based on mixup for automatic speech recognition (ASR). MixSpeech trains an ASR model by taking…
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation
Jinglin Liu, Yi Ren, Xu Tan +4
Non-autoregressive translation (NAT) achieves faster inference speed but at the cost of worse accuracy compared with autoregressive translation (AT). Since AT and NAT can share mod…
A Study of Non-autoregressive Model for Sequence Generation
Yi Ren, Jinglin Liu, Xu Tan +3
Non-autoregressive (NAR) models generate all the tokens of a sequence in parallel, resulting in faster generation speed compared to their autoregressive (AR) counterparts but at th…
A Study of Multilingual Neural Machine Translation
Xu Tan, Yichong Leng, Jiale Chen +3
Multilingual neural machine translation (NMT) has recently been investigated from different aspects (e.g., pivot translation, zero-shot translation, fine-tuning, or training from s…