IsoChronoMeter: A simple and effective isochronic translation evaluation metric
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916439715217408 |
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| author | Rozanov, Nikolai Pankov, Vikentiy Mukhutdinov, Dmitrii Vypirailenko, Dima |
| author_facet | Rozanov, Nikolai Pankov, Vikentiy Mukhutdinov, Dmitrii Vypirailenko, Dima |
| contents | 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}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_11127 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | IsoChronoMeter: A simple and effective isochronic translation evaluation metric Rozanov, Nikolai Pankov, Vikentiy Mukhutdinov, Dmitrii Vypirailenko, Dima Computation and Language 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}. |
| title | IsoChronoMeter: A simple and effective isochronic translation evaluation metric |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2410.11127 |