MAVL: A Multilingual Audio-Video Lyrics Dataset for Animated Song Translation (2025.emnlp-main)
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| Challenge: | Experimental results show that multimodal, multimodal approaches to lyrics translation are more effective than text-only approaches. |
| Approach: | They propose a multilingual, multimodal benchmark for singable lyrics translation . they propose syllable-constrained audio-video LLM with Chain-of-Thought . |
| Outcome: | The proposed system outperforms text-based models in singability and contextual accuracy. |
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| Challenge: | Song translation requires both translation of lyrics and alignment of music notes . human translators of songs need to have a mastery of cultural traditions and the poetic usage of both source and target languages . |
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| Challenge: | Existing song translation approaches prioritize singability constraints at the expense of translation quality, which is crucial for musicals. |
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| Challenge: | Existing studies on lyrics translation have relied on fine-tuning open-source language models. |
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| Challenge: | Existing automatic song translation systems for tonal languages do not match the number of notes and beat the original rhythm of the song. |
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Kento Watanabe, Yuichiroh Matsubayashi, Satoru Fukayama, Masataka Goto, Kentaro Inui, Tomoyasu Nakano
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