Stream-level Latency Evaluation for Simultaneous Machine Translation
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Abstract (arXiv)
Simultaneous machine translation has recently gained traction thanks to significant quality improvements and the advent of streaming applications. Simultaneous translation systems need to find a trade-off between translation quality and response time, and with this purpose multiple latency measures have been proposed. However, latency evaluations for simultaneous translation are estimated at the sentence level, not taking into account the sequential nature of a streaming scenario. Indeed, these sentence-level latency measures are not well suited for continuous stream translation resulting in figures that are not coherent with the simultaneous translation policy of the system being assessed. This work proposes a stream-level adaptation of the current latency measures based on a re-segmentation approach applied to the output translation, that is successfully evaluated on streaming conditions for a reference IWSLT task.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 5 of its 17 references that are in the map. First posted on arXiv 18 Apr 2021.
Builds on
5 of 17 references.
References · 5
- 2017Attention Is All You Needcited by 59,932
- 2016Can neural machine translation do simultaneous translation?cited by 85
- 2020Efficient Wait-k Models for Simultaneous Machine Translationcited by 59
- 2019Thinking Slow about Latency Evaluation for Simultaneous Machine Translationcited by 28
- 2020ON-TRAC Consortium for End-to-End and Simultaneous Speech Translation Challenge Tasks at IWSLT 2020cited by 9
Built on by
Citing papers per year: 2022: 2; 2023: 5; 2024: 4; 2025: 1.
12 papers.
- 2024StreamAtt: Direct Streaming Speech-to-Text Translation with Attention-based Audio History Selectioncited by 19
- 2022Average Token Delay: A Latency Metric for Simultaneous Translationcited by 15
- 2023Learning Optimal Policy for Simultaneous Machine Translation via Binary Searchcited by 15
- 2022From Simultaneous to Streaming Machine Translation by Leveraging Streaming Historycited by 9
- 2023Long-Form End-to-End Speech Translation via Latent Alignment Segmentationcited by 6
- 2025Better Late Than Never: Meta-Evaluation of Latency Metrics for Simultaneous Speech-to-Text Translationcited by 4
- 2023Long-form Simultaneous Speech Translation: Thesis Proposalcited by 3
- 2023Segmentation-Free Streaming Machine Translationcited by 2
- 2023Average Token Delay: A Duration-aware Latency Metric for Simultaneous Translationcited by 2
- 2024Fixed and Adaptive Simultaneous Machine Translation Strategies Using Adapterscited by 2
- 2024Assessing Latency in ASR Systems: A Methodological Perspective for Real-Time Usecited by 2
- 2024CA*: Addressing Evaluation Pitfalls in Computation-Aware Latency for Simultaneous Speech Translationcited by 0
- 2025Better Late Than Never: Meta-Evaluation of Latency Metrics for Simultaneous Speech-to-Text Translation22 Sep 2025
- 2024CA*: Addressing Evaluation Pitfalls in Computation-Aware Latency for Simultaneous Speech Translation21 Oct 2024
- 2024Assessing Latency in ASR Systems: A Methodological Perspective for Real-Time Use9 Sep 2024
- 2024Fixed and Adaptive Simultaneous Machine Translation Strategies Using Adapters18 Jul 2024
- 2024StreamAtt: Direct Streaming Speech-to-Text Translation with Attention-based Audio History Selection10 Jun 2024
- 2023Average Token Delay: A Duration-aware Latency Metric for Simultaneous Translation24 Nov 2023
- 2023Long-form Simultaneous Speech Translation: Thesis Proposal17 Oct 2023
- 2023Segmentation-Free Streaming Machine Translation26 Sep 2023
- 2023Long-Form End-to-End Speech Translation via Latent Alignment Segmentation20 Sep 2023
- 2023Learning Optimal Policy for Simultaneous Machine Translation via Binary Search22 May 2023
- 2022Average Token Delay: A Latency Metric for Simultaneous Translation22 Nov 2022
- 2022From Simultaneous to Streaming Machine Translation by Leveraging Streaming History4 Mar 2022