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        <title>Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation</title>
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    <abstract>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.</abstract>
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%0 Conference Proceedings
%T Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation
%A Papi, Sara
%A Gaido, Marco
%A Negri, Matteo
%A Turchi, Marco
%Y Ive, Julia
%Y Zhang, Ruiqing
%S Proceedings of the Third Workshop on Automatic Simultaneous Translation
%D 2022
%8 July
%I Association for Computational Linguistics
%C Online
%F papi-etal-2022-generation
%X 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.
%R 10.18653/v1/2022.autosimtrans-1.2
%U https://aclanthology.org/2022.autosimtrans-1.2
%U https://doi.org/10.18653/v1/2022.autosimtrans-1.2
%P 12-17

Markdown (Informal)

[Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation](https://aclanthology.org/2022.autosimtrans-1.2) (Papi et al., AutoSimTrans 2022)

• Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation (Papi et al., AutoSimTrans 2022)

ACL

• Sara Papi, Marco Gaido, Matteo Negri, and Marco Turchi. 2022. Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation. In Proceedings of the Third Workshop on Automatic Simultaneous Translation, pages 12–17, Online. Association for Computational Linguistics.