# Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation

arXiv: https://arxiv.org/abs/2206.05807 · HTML: https://mlsanity.com/paper/2206.05807/

## Key facts

- Cited by 57 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 23 references that are in the map.
- First posted on arXiv 12 Jun 2022.

## Builds on (most cited first, 14 of 14)

- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [Learning to Translate in Real-time with Neural Machine Translation](https://mlsanity.com/paper/1610.00388/) (2016)
- [Exploring Architectures, Data and Units For Streaming End-to-End Speech Recognition with RNN-Transducer](https://mlsanity.com/paper/1801.00841/) (2018)
- [SimulEval: An Evaluation Toolkit for Simultaneous Translation](https://mlsanity.com/paper/2007.16193/) (2020)
- [Can neural machine translation do simultaneous translation?](https://mlsanity.com/paper/1606.02012/) (2016)
- [SimulMT to SimulST: Adapting Simultaneous Text Translation to End-to-End Simultaneous Speech Translation](https://mlsanity.com/paper/2011.02048/) (2020)
- [RealTranS: End-to-End Simultaneous Speech Translation with Convolutional Weighted-Shrinking Transformer](https://mlsanity.com/paper/2106.04833/) (2021)
- [Direct Simultaneous Speech-to-Text Translation Assisted by Synchronized Streaming ASR](https://mlsanity.com/paper/2106.06636/) (2021)
- [Thinking Slow about Latency Evaluation for Simultaneous Machine Translation](https://mlsanity.com/paper/1906.00048/) (2019)
- [Does Simultaneous Speech Translation need Simultaneous Models?](https://mlsanity.com/paper/2204.03783/) (2022)
- [Efficient yet Competitive Speech Translation: FBK@IWSLT2022](https://mlsanity.com/paper/2205.02629/) (2022)
- [Simultaneous Speech Translation for Live Subtitling: from Delay to Display](https://mlsanity.com/paper/2107.08807/) (2021)
- [Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-English](https://mlsanity.com/paper/2006.00814/) (2020)
- [Visualization: the missing factor in Simultaneous Speech Translation](https://mlsanity.com/paper/2111.00514/) (2021)

## Built on by (most cited first, 30 of 57)

- [AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation](https://mlsanity.com/paper/2305.11408/) (2023)
- [TransLLaMa: LLM-based Simultaneous Translation System](https://mlsanity.com/paper/2402.04636/) (2024)
- [Attention as a Guide for Simultaneous Speech Translation](https://mlsanity.com/paper/2212.07850/) (2022)
- [StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learning](https://mlsanity.com/paper/2406.03049/) (2024)
- [Hybrid Transducer and Attention based Encoder-Decoder Modeling for Speech-to-Text Tasks](https://mlsanity.com/paper/2305.03101/) (2023)
- [StreamAtt: Direct Streaming Speech-to-Text Translation with Attention-based Audio History Selection](https://mlsanity.com/paper/2406.06097/) (2024)
- [BESTOW: Efficient and Streamable Speech Language Model with the Best of Two Worlds in GPT and T5](https://mlsanity.com/paper/2406.19954/) (2024)
- [How "Real" is Your Real-Time Simultaneous Speech-to-Text Translation System?](https://mlsanity.com/paper/2412.18495/) (2024)
- [Average Token Delay: A Latency Metric for Simultaneous Translation](https://mlsanity.com/paper/2211.13173/) (2022)
- [High-Fidelity Simultaneous Speech-To-Speech Translation](https://mlsanity.com/paper/2502.03382/) (2025)
- [Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agent](https://mlsanity.com/paper/2407.21646/) (2024)
- [Efficient and Adaptive Simultaneous Speech Translation with Fully Unidirectional Architecture](https://mlsanity.com/paper/2504.11809/) (2025)
- [Simultaneous Masking, Not Prompting Optimization: A Paradigm Shift in Fine-tuning LLMs for Simultaneous Translation](https://mlsanity.com/paper/2405.10443/) (2024)
- [A Non-autoregressive Generation Framework for End-to-End Simultaneous Speech-to-Speech Translation](https://mlsanity.com/paper/2406.06937/) (2024)
- [Simultaneous Machine Translation with Large Language Models](https://mlsanity.com/paper/2309.06706/) (2023)
- [Seed LiveInterpret 2.0: End-to-end Simultaneous Speech-to-speech Translation with Your Voice](https://mlsanity.com/paper/2507.17527/) (2025)
- [Incremental Blockwise Beam Search for Simultaneous Speech Translation with Controllable Quality-Latency Tradeoff](https://mlsanity.com/paper/2309.11379/) (2023)
- [InfiniSST: Simultaneous Translation of Unbounded Speech with Large Language Model](https://mlsanity.com/paper/2503.02969/) (2025)
- [FASST: Fast LLM-based Simultaneous Speech Translation](https://mlsanity.com/paper/2408.09430/) (2024)
- [SimulPL: Aligning Human Preferences in Simultaneous Machine Translation](https://mlsanity.com/paper/2502.00634/) (2025)
- [Simultaneous Speech-to-Speech Translation Without Aligned Data](https://mlsanity.com/paper/2602.11072/) (2026)
- [Token-Level Serialized Output Training for Joint Streaming ASR and ST Leveraging Textual Alignments](https://mlsanity.com/paper/2307.03354/) (2023)
- [Long-Form End-to-End Speech Translation via Latent Alignment Segmentation](https://mlsanity.com/paper/2309.11384/) (2023)
- [Direct Models for Simultaneous Translation and Automatic Subtitling: FBK@IWSLT2023](https://mlsanity.com/paper/2309.15554/) (2023)
- [Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models](https://mlsanity.com/paper/2312.04691/) (2023)
- [Joint Speech Translation and Named Entity Recognition](https://mlsanity.com/paper/2210.11987/) (2022)
- [Label-Synchronous Neural Transducer for E2E Simultaneous Speech Translation](https://mlsanity.com/paper/2406.04541/) (2024)
- [LLMs Can Achieve High-quality Simultaneous Machine Translation as Efficiently as Offline](https://mlsanity.com/paper/2504.09570/) (2025)
- [Leveraging Timestamp Information for Serialized Joint Streaming Recognition and Translation](https://mlsanity.com/paper/2310.14806/) (2023)
- [Overcoming Non-monotonicity in Transducer-based Streaming Generation](https://mlsanity.com/paper/2411.17170/) (2024)

## Abstract (arXiv)

Simultaneous speech translation (SimulST) systems aim at generating their output with the lowest possible latency, which is normally computed in terms of Average Lagging (AL). In this paper we highlight that, despite its widespread adoption, AL provides underestimated scores for systems that generate longer predictions compared to the corresponding references. We also show that this problem has practical relevance, as recent SimulST systems have indeed a tendency to over-generate. As a solution, we propose LAAL (Length-Adaptive Average Lagging), a modified version of the metric that takes into account the over-generation phenomenon and allows for unbiased evaluation of both under-/over-generating systems.