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        <namePart type="given">Nikolai</namePart>
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        <namePart type="given">Vikentiy</namePart>
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            <title>Proceedings of the Ninth Conference on Machine Translation</title>
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    <abstract>Machine translation (MT) has come a long way and is readily employed in production systems to serve millions of users daily. With the recent advances in generative AI, a new form of translation is becoming possible - video dubbing. This work motivates the importance of isochronic translation, especially in the context of automatic dubbing, and introduces ‘IsoChronoMeter’ (ICM). ICM is a simple yet effective metric to measure isochrony of translations in a scalable and resource-efficient way without the need for gold data, based on state-of-the-art text-to-speech (TTS) duration predictors. We motivate IsoChronoMeter and demonstrate its effectiveness. Using ICM we demonstrate the shortcomings of state-of-the-art translation systems and show the need for new methods. We release the code at this URL: https://github.com/braskai/isochronometer.</abstract>
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%0 Conference Proceedings
%T IsoChronoMeter: A Simple and Effective Isochronic Translation Evaluation Metric
%A Rozanov, Nikolai
%A Pankov, Vikentiy
%A Mukhutdinov, Dmitrii
%A Vypirailenko, Dima
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Ninth Conference on Machine Translation
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F rozanov-etal-2024-isochronometer
%X Machine translation (MT) has come a long way and is readily employed in production systems to serve millions of users daily. With the recent advances in generative AI, a new form of translation is becoming possible - video dubbing. This work motivates the importance of isochronic translation, especially in the context of automatic dubbing, and introduces ‘IsoChronoMeter’ (ICM). ICM is a simple yet effective metric to measure isochrony of translations in a scalable and resource-efficient way without the need for gold data, based on state-of-the-art text-to-speech (TTS) duration predictors. We motivate IsoChronoMeter and demonstrate its effectiveness. Using ICM we demonstrate the shortcomings of state-of-the-art translation systems and show the need for new methods. We release the code at this URL: https://github.com/braskai/isochronometer.
%U https://aclanthology.org/2024.wmt-1.29
%P 372-379

Markdown (Informal)

[IsoChronoMeter: A Simple and Effective Isochronic Translation Evaluation Metric](https://aclanthology.org/2024.wmt-1.29) (Rozanov et al., WMT 2024)

• IsoChronoMeter: A Simple and Effective Isochronic Translation Evaluation Metric (Rozanov et al., WMT 2024)

ACL

• Nikolai Rozanov, Vikentiy Pankov, Dmitrii Mukhutdinov, and Dima Vypirailenko. 2024. IsoChronoMeter: A Simple and Effective Isochronic Translation Evaluation Metric. In Proceedings of the Ninth Conference on Machine Translation, pages 372–379, Miami, Florida, USA. Association for Computational Linguistics.