Search Results for author:
Found 12 papers, 1 papers with code
CSP:Code-Switching Pre-training for Neural Machine Translation
Unlike traditional pre-training method which randomly masks some fragments of the input sentence, the proposed CSP randomly replaces some words in the source sentence with their translation words in the target language.
PM-MMUT: Boosted Phone-mask Data Augmentation using Multi-Modeling Unit Training for Phonetic-Reduction-Robust E2E Speech Recognition
To boost the performance of PMT, we propose multi-modeling unit training (MMUT) architecture fusion with PMT (PM-MMUT).
Adversarial Sample Detection for Speaker Verification by Neural Vocoders
We also show that the neural vocoder adopted in the detection framework is dataset-independent.
Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
To our knowledge, we are the first to develop an end-to-end ST system that achieves comparable or even better BLEU performance than the cascaded ST counterpart when large-scale ASR and MT data is available.
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation
This eases training by highlighting easy samples that the current model has enough competence to learn.
Code-switching pre-training for neural machine translation
Unlike traditional pre-training method which randomly masks some fragments of the input sentence, the proposed CSP randomly replaces some words in the source sentence with their translation words in the target language.
Cognitive Representation Learning of Self-Media Online Article Quality
The automatic quality assessment of self-media online articles is an urgent and new issue, which is of great value to the online recommendation and search.
A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection
Chinese keyword spotting is a challenging task as there is no visual blank for Chinese words.
Utterance-level end-to-end language identification using attention-based CNN-BLSTM
In this paper, we present an end-to-end language identification framework, the attention-based Convolutional Neural Network-Bidirectional Long-short Term Memory (CNN-BLSTM).
TencentFmRD Neural Machine Translation for WMT18
Our systems are neural machine translation systems trained with our original system TenTrans.
Addressing Domain Adaptation for Chinese Word Segmentation with Global Recurrent Structure
Boundary features are widely used in traditional Chinese Word Segmentation (CWS) methods as they can utilize unlabeled data to help improve the Out-of-Vocabulary (OOV) word recognition performance.
Bi-LSTM Neural Networks for Chinese Grammatical Error Diagnosis
Grammatical Error Diagnosis for Chinese has always been a challenge for both foreign learners and NLP researchers, for the variousity of grammar and the flexibility of expression.
