49 citations · 104 across the 6 of their papers we have counts for
8 papers
PolyVoice: Language Models for Speech to Speech Translation
Qianqian Dong, Zhiying Huang, Qiao Tian +15
We propose PolyVoice, a language model-based framework for speech-to-speech translation (S2ST) system. Our framework consists of two language models: a translation language model a…
M3ST: Mix at Three Levels for Speech Translation
Xuxin Cheng, Qianqian Dong, Fengpeng Yue +3
How to solve the data scarcity problem for end-to-end speech-to-text translation (ST)? It's well known that data augmentation is an efficient method to improve performance for many…
Leveraging Pseudo-labeled Data to Improve Direct Speech-to-Speech Translation
Qianqian Dong, Fengpeng Yue, Tom Ko +3
Direct Speech-to-speech translation (S2ST) has drawn more and more attention recently. The task is very challenging due to data scarcity and complex speech-to-speech mapping. In th…
The Volctrans Neural Speech Translation System for IWSLT 2021
Chengqi Zhao, Zhicheng Liu, Jian Tong +6
This paper describes the systems submitted to IWSLT 2021 by the Volctrans team. We participate in the offline speech translation and text-to-text simultaneous translation tracks. F…
"Listen, Understand and Translate": Triple Supervision Decouples End-to-end Speech-to-text Translation
Qianqian Dong, Rong Ye, Mingxuan Wang +4
An end-to-end speech-to-text translation (ST) takes audio in a source language and outputs the text in a target language. Existing methods are limited by the amount of parallel cor…
CLUE: A Chinese Language Understanding Evaluation Benchmark
Liang Xu, Hai Hu, Xuanwei Zhang +29
The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks. These com…