1.9k citations · 2.9k across the 17 of their papers we have counts for
17 papers
TESSP: Text-Enhanced Self-Supervised Speech Pre-training
Zhuoyuan Yao, Shuo Ren, Sanyuan Chen +3
Self-supervised speech pre-training empowers the model with the contextual structure inherent in the speech signal while self-supervised text pre-training empowers the model with l…
RAPO: An Adaptive Ranking Paradigm for Bilingual Lexicon Induction
Zhoujin Tian, Chaozhuo Li, Shuo Ren +8
Bilingual lexicon induction induces the word translations by aligning independently trained word embeddings in two languages. Existing approaches generally focus on minimizing the…
SpeechLM: Enhanced Speech Pre-Training with Unpaired Textual Data
Ziqiang Zhang, Sanyuan Chen, Long Zhou +8
How to boost speech pre-training with textual data is an unsolved problem due to the fact that speech and text are very different modalities with distinct characteristics. In this…
Speech Pre-training with Acoustic Piece
Shuo Ren, Shujie Liu, Yu Wu +2
Previous speech pre-training methods, such as wav2vec2.0 and HuBERT, pre-train a Transformer encoder to learn deep representations from audio data, with objectives predicting eithe…
Optimizing Alignment of Speech and Language Latent Spaces for End-to-End Speech Recognition and Understanding
Wei Wang, Shuo Ren, Yao Qian +4
The advances in attention-based encoder-decoder (AED) networks have brought great progress to end-to-end (E2E) automatic speech recognition (ASR). One way to further improve the pe…
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
Sanyuan Chen, Chengyi Wang, Zhengyang Chen +15
Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing tasks. As speech signal contai…
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
Junyi Ao, Rui Wang, Long Zhou +11
Motivated by the success of T5 (Text-To-Text Transfer Transformer) in pre-trained natural language processing models, we propose a unified-modal SpeechT5 framework that explores th…
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Shuai Lu, Daya Guo, Shuo Ren +19
Benchmark datasets have a significant impact on accelerating research in programming language tasks. In this paper, we introduce CodeXGLUE, a benchmark dataset to foster machine le…
CodeBLEU: a Method for Automatic Evaluation of Code Synthesis
Shuo Ren, Daya Guo, Shuai Lu +7
Evaluation metrics play a vital role in the growth of an area as it defines the standard of distinguishing between good and bad models. In the area of code synthesis, the commonly…
GraphCodeBERT: Pre-training Code Representations with Data Flow
Daya Guo, Shuo Ren, Shuai Lu +15
Pre-trained models for programming language have achieved dramatic empirical improvements on a variety of code-related tasks such as code search, code completion, code summarizatio…
Semantic Mask for Transformer based End-to-End Speech Recognition
Chengyi Wang, Yu Wu, Yujiao Du +7
Attention-based encoder-decoder model has achieved impressive results for both automatic speech recognition (ASR) and text-to-speech (TTS) tasks. This approach takes advantage of t…
Explicit Cross-lingual Pre-training for Unsupervised Machine Translation
Shuo Ren, Yu Wu, Shujie Liu +2
Pre-training has proven to be effective in unsupervised machine translation due to its ability to model deep context information in cross-lingual scenarios. However, the cross-ling…
Unsupervised Neural Machine Translation with SMT as Posterior Regularization
Shuo Ren, Zhirui Zhang, Shujie Liu +2
Without real bilingual corpus available, unsupervised Neural Machine Translation (NMT) typically requires pseudo parallel data generated with the back-translation method for the mo…
Style Transfer as Unsupervised Machine Translation
Zhirui Zhang, Shuo Ren, Shujie Liu +5
Language style transferring rephrases text with specific stylistic attributes while preserving the original attribute-independent content. One main challenge in learning a style tr…
Regularizing Neural Machine Translation by Target-bidirectional Agreement
Zhirui Zhang, Shuangzhi Wu, Shujie Liu +3
Although Neural Machine Translation (NMT) has achieved remarkable progress in the past several years, most NMT systems still suffer from a fundamental shortcoming as in other seque…
Triangular Architecture for Rare Language Translation
Shuo Ren, Wenhu Chen, Shujie Liu +3
Neural Machine Translation (NMT) performs poor on the low-resource language pair , especially when is a rare language. By introducing another rich language , we propo…
Generative Bridging Network in Neural Sequence Prediction
Wenhu Chen, Guanlin Li, Shuo Ren +4
In order to alleviate data sparsity and overfitting problems in maximum likelihood estimation (MLE) for sequence prediction tasks, we propose the Generative Bridging Network (GBN),…