62 citations · 210 across the 18 of their papers we have counts for
18 papers
Findings of the IWSLT 2024 Evaluation Campaign
Ibrahim Said Ahmad, Antonios Anastasopoulos, Ondřej Bojar +42
This paper reports on the shared tasks organized by the 21st IWSLT Conference. The shared tasks address 7 scientific challenges in spoken language translation: simultaneous and off…
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Ye Bai, Jingping Chen, Jitong Chen +52
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…
Revisiting Interpolation Augmentation for Speech-to-Text Generation
Chen Xu, Jie Wang, Xiaoqian Liu +6
Speech-to-text (S2T) generation systems frequently face challenges in low-resource scenarios, primarily due to the lack of extensive labeled datasets. One emerging solution is cons…
Speech Translation with Large Language Models: An Industrial Practice
Zhichao Huang, Rong Ye, Tom Ko +4
Given the great success of large language models (LLMs) across various tasks, in this paper, we introduce LLM-ST, a novel and effective speech translation model constructed upon a…
Bridging the Gaps of Both Modality and Language: Synchronous Bilingual CTC for Speech Translation and Speech Recognition
Chen Xu, Xiaoqian Liu, Erfeng He +6
In this study, we present synchronous bilingual Connectionist Temporal Classification (CTC), an innovative framework that leverages dual CTC to bridge the gaps of both modality and…
Recent Advances in Direct Speech-to-text Translation
Chen Xu, Rong Ye, Qianqian Dong +5
Recently, speech-to-text translation has attracted more and more attention and many studies have emerged rapidly. In this paper, we present a comprehensive survey on direct speech…
MOSPC: MOS Prediction Based on Pairwise Comparison
Kexin Wang, Yunlong Zhao, Qianqian Dong +2
As a subjective metric to evaluate the quality of synthesized speech, Mean opinion score~(MOS) usually requires multiple annotators to score the same speech. Such an annotation app…
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…
CTC-based Non-autoregressive Speech Translation
Chen Xu, Xiaoqian Liu, Xiaowen Liu +9
Combining end-to-end speech translation (ST) and non-autoregressive (NAR) generation is promising in language and speech processing for their advantages of less error propagation 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…
Learning When to Translate for Streaming Speech
Qianqian Dong, Yaoming Zhu, Mingxuan Wang +1
How to find proper moments to generate partial sentence translation given a streaming speech input? Existing approaches waiting-and-translating for a fixed duration often break the…
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…
Consecutive Decoding for Speech-to-text Translation
Qianqian Dong, Mingxuan Wang, Hao Zhou +3
Speech-to-text translation (ST), which directly translates the source language speech to the target language text, has attracted intensive attention recently. However, the combinat…
"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…
CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language Model
Liang Xu, Xuanwei Zhang, Qianqian Dong
In this paper, we introduce the Chinese corpus from CLUE organization, CLUECorpus2020, a large-scale corpus that can be used directly for self-supervised learning such as pre-train…
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
Liang Xu, Yu tong, Qianqian Dong +7
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese. CLUENER2020 contains…