mlsanityData to 7 Oct 2026

Average Token Delay: A Latency Metric for Simultaneous Translation

arXiv 2211.13173 ↗First posted 22 Nov 2022cs.CL cs.SDcited by 15

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Abstract (arXiv)

Simultaneous translation is a task in which translation begins before the speaker has finished speaking. In its evaluation, we have to consider the latency of the translation in addition to the quality. The latency is preferably as small as possible for users to comprehend what the speaker says with a small delay. Existing latency metrics focus on when the translation starts but do not consider adequately when the translation ends. This means such metrics do not penalize the latency caused by a long translation output, which actually delays users' comprehension. In this work, we propose a novel latency evaluation metric called Average Token Delay (ATD) that focuses on the end timings of partial translations in simultaneous translation. We discuss the advantage of ATD using simulated examples and also investigate the differences between ATD and Average Lagging with simultaneous translation experiments.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 7 of its 12 references that are in the map. First posted on arXiv 22 Nov 2022.

Builds on

7 of 12 references.

References · 7

  1. 2019Monotonic Infinite Lookback Attention for Simultaneous Machine Translationcited by 103
  2. 2016Learning to Translate in Real-time with Neural Machine Translationcited by 97
  3. 2020SimulEval: An Evaluation Toolkit for Simultaneous Translationcited by 94
  4. 2016Can neural machine translation do simultaneous translation?cited by 85
  5. 2022Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translationcited by 56
  6. 2021Stream-level Latency Evaluation for Simultaneous Machine Translationcited by 12
  7. 2021Simultaneous Neural Machine Translation with Constituent Label Predictioncited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 6; 2025: 4; 2026: 2.

15 papers.

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  1. 2024StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learningcited by 20
  2. 2024How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?cited by 17
  3. 2023Tagged End-to-End Simultaneous Speech Translation Training using Simultaneous Interpretation Datacited by 6
  4. 2023Direct Models for Simultaneous Translation and Automatic Subtitling: FBK@IWSLT2023cited by 6
  5. 2024Recent Advances in End-to-End Simultaneous Speech Translationcited by 5
  6. 2025Better Late Than Never: Meta-Evaluation of Latency Metrics for Simultaneous Speech-to-Text Translationcited by 4
  7. 2024Simultaneous Interpretation Corpus Construction by Large Language Models in Distant Language Paircited by 3
  8. 2025SimulS2S-LLM: Unlocking Simultaneous Inference of Speech LLMs for Speech-to-Speech Translationcited by 3
  9. 2023Average Token Delay: A Duration-aware Latency Metric for Simultaneous Translationcited by 2
  10. 2025Chunk Based Speech Pre-training with High Resolution Finite Scalar Quantizationcited by 2
  11. 2024SimulSeamless: FBK at IWSLT 2024 Simultaneous Speech Translationcited by 1
  12. 2026Redefining Machine Simultaneous Interpretation: From Incremental Translation to Human-Like Strategiescited by 1
3 more
  1. 2024CA*: Addressing Evaluation Pitfalls in Computation-Aware Latency for Simultaneous Speech Translationcited by 0
  2. 2025Redefining Machine Simultaneous Interpretation: From Incremental Translation to Human-Like Strategiescited by 0
  3. 2026Rubric-Aligned Disentangled Evaluation of Human Simultaneous Interpretingcited by 0