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arXiv · 2410.11127

IsoChronoMeter: A simple and effective isochronic translation evaluation metric

Nikolai Rozanov·Vikentiy Pankov·Dmitrii Mukhutdinov·Dima Vypirailenko
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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: \url{https://github.com/braskai/isochronometer}.

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Nikolai Rozanov, Vikentiy Pankov, Dmitrii Mukhutdinov, Dima Vypirailenko. 2024-10-14. IsoChronoMeter: A simple and effective isochronic translation evaluation metric. https://arxiv.org/abs/2410.11127

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