Wait-info Policy: Balancing Source and Target at Information Level for Simultaneous Machine Translation
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Abstract (arXiv)
Simultaneous machine translation (SiMT) outputs the translation while receiving the source inputs, and hence needs to balance the received source information and translated target information to make a reasonable decision between waiting for inputs or outputting translation. Previous methods always balance source and target information at the token level, either directly waiting for a fixed number of tokens or adjusting the waiting based on the current token. In this paper, we propose a Wait-info Policy to balance source and target at the information level. We first quantify the amount of information contained in each token, named info. Then during simultaneous translation, the decision of waiting or outputting is made based on the comparison results between the total info of previous target outputs and received source inputs. Experiments show that our method outperforms strong baselines under and achieves better balance via the proposed info.
Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 20 of its 35 references that are in the map. First posted on arXiv 20 Oct 2022.
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20 of 35 references.
References · 20
- 2017Attention Is All You Needcited by 60,361
- 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,918
- 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,488
- 2019Monotonic Infinite Lookback Attention for Simultaneous Machine Translationcited by 104
- 2016Learning to Translate in Real-time with Neural Machine Translationcited by 97
- 2019Monotonic Multihead Attentioncited by 93
- 2016Can neural machine translation do simultaneous translation?cited by 86
- 2020Efficient Wait-k Models for Simultaneous Machine Translationcited by 61
- 2020Norm-Based Curriculum Learning for Neural Machine Translationcited by 60
- 2020Simultaneous Translation Policies: From Fixed to Adaptivecited by 43
- 2019Simpler and Faster Learning of Adaptive Policies for Simultaneous Translationcited by 37
- 2021Universal Simultaneous Machine Translation with Mixture-of-Experts Wait-k Policycited by 32
8 more
- 2020Future-Guided Incremental Transformer for Simultaneous Translationcited by 30
- 2022Modeling Dual Read/Write Paths for Simultaneous Machine Translationcited by 21
- 2021Modeling Concentrated Cross-Attention for Neural Machine Translation with Gaussian Mixture Modelcited by 18
- 2022Gaussian Multi-head Attention for Simultaneous Machine Translationcited by 17
- 2022Reducing Position Bias in Simultaneous Machine Translation with Length-Aware Frameworkcited by 16
- 2018Learning When to Concentrate or Divert Attention: Self-Adaptive Attention Temperature for Neural Machine Translationcited by 10
- 2019Interrogating the Explanatory Power of Attention in Neural Machine Translationcited by 7
- 2022Conditional Bilingual Mutual Information Based Adaptive Training for Neural Machine Translationcited by 6
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Citing papers per year: 2022: 2; 2023: 10; 2024: 4.
16 papers.
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- 2022Information-Transport-based Policy for Simultaneous Translationcited by 40
- 2023Hidden Markov Transformer for Simultaneous Machine Translationcited by 25
- 2023End-to-End Simultaneous Speech Translation with Differentiable Segmentationcited by 22
- 2024StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learningcited by 21
- 2023Learning Optimal Policy for Simultaneous Machine Translation via Binary Searchcited by 15
- 2022Turning Fixed to Adaptive: Integrating Post-Evaluation into Simultaneous Machine Translationcited by 14
- 2024Decoder-only Streaming Transformer for Simultaneous Translationcited by 11
- 2023Glancing Future for Simultaneous Machine Translationcited by 10
- 2023Simultaneous Machine Translation with Large Language Modelscited by 9
- 2023Simultaneous Machine Translation with Tailored Referencecited by 9
- 2023Adaptive Policy with Wait-k Model for Simultaneous Translationcited by 9
- 2023Unified Segment-to-Segment Framework for Simultaneous Sequence Generationcited by 6
4 more
- 2024Conversational SimulMT: Efficient Simultaneous Translation with Large Language Modelscited by 4
- 2023Enhanced Simultaneous Machine Translation with Word-level Policiescited by 2
- 2024PsFuture: A Pseudo-Future-based Zero-Shot Adaptive Policy for Simultaneous Machine Translationcited by 2
- 2023Context Consistency between Training and Testing in Simultaneous Machine Translationcited by 0
- 2024PsFuture: A Pseudo-Future-based Zero-Shot Adaptive Policy for Simultaneous Machine Translation5 Oct 2024
- 2024Decoder-only Streaming Transformer for Simultaneous Translation6 Jun 2024
- 2024StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learning5 Jun 2024
- 2024Conversational SimulMT: Efficient Simultaneous Translation with Large Language Models16 Feb 2024
- 2023Context Consistency between Training and Testing in Simultaneous Machine Translation13 Nov 2023
- 2023Unified Segment-to-Segment Framework for Simultaneous Sequence Generation27 Oct 2023
- 2023Enhanced Simultaneous Machine Translation with Word-level Policies25 Oct 2023
- 2023Adaptive Policy with Wait-k Model for Simultaneous Translation23 Oct 2023
- 2023Simultaneous Machine Translation with Tailored Reference20 Oct 2023
- 2023Simultaneous Machine Translation with Large Language Models13 Sep 2023
- 2023Glancing Future for Simultaneous Machine Translation12 Sep 2023
- 2023End-to-End Simultaneous Speech Translation with Differentiable Segmentation25 May 2023
4 more
- 2023Learning Optimal Policy for Simultaneous Machine Translation via Binary Search22 May 2023
- 2023Hidden Markov Transformer for Simultaneous Machine Translation1 Mar 2023
- 2022Information-Transport-based Policy for Simultaneous Translation22 Oct 2022
- 2022Turning Fixed to Adaptive: Integrating Post-Evaluation into Simultaneous Machine Translation21 Oct 2022
- 2022Information-Transport-based Policy for Simultaneous Translationcited by 40
- 2023Hidden Markov Transformer for Simultaneous Machine Translationcited by 25
- 2023End-to-End Simultaneous Speech Translation with Differentiable Segmentationcited by 22
- 2024StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learningcited by 21
- 2023Learning Optimal Policy for Simultaneous Machine Translation via Binary Searchcited by 15
- 2022Turning Fixed to Adaptive: Integrating Post-Evaluation into Simultaneous Machine Translationcited by 14
- 2024Decoder-only Streaming Transformer for Simultaneous Translationcited by 11
- 2023Glancing Future for Simultaneous Machine Translationcited by 10
- 2023Simultaneous Machine Translation with Large Language Modelscited by 9
- 2023Simultaneous Machine Translation with Tailored Referencecited by 9
- 2023Adaptive Policy with Wait-k Model for Simultaneous Translationcited by 9
- 2023Unified Segment-to-Segment Framework for Simultaneous Sequence Generationcited by 6
12 most cited of 16 All 16 (JSON)
- 2024PsFuture: A Pseudo-Future-based Zero-Shot Adaptive Policy for Simultaneous Machine Translation5 Oct 2024
- 2024Decoder-only Streaming Transformer for Simultaneous Translation6 Jun 2024
- 2024StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learning5 Jun 2024
- 2024Conversational SimulMT: Efficient Simultaneous Translation with Large Language Models16 Feb 2024
- 2023Context Consistency between Training and Testing in Simultaneous Machine Translation13 Nov 2023
- 2023Unified Segment-to-Segment Framework for Simultaneous Sequence Generation27 Oct 2023
- 2023Enhanced Simultaneous Machine Translation with Word-level Policies25 Oct 2023
- 2023Adaptive Policy with Wait-k Model for Simultaneous Translation23 Oct 2023
- 2023Simultaneous Machine Translation with Tailored Reference20 Oct 2023
- 2023Simultaneous Machine Translation with Large Language Models13 Sep 2023
- 2023Glancing Future for Simultaneous Machine Translation12 Sep 2023
- 2023End-to-End Simultaneous Speech Translation with Differentiable Segmentation25 May 2023
12 newest of 16 All 16 (JSON)