Translation of Music

Desblache, Lucile

doi:10.2307/j.ctvbtzp7q.12

Cited by 2 publications

(2 citation statements)

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“…Automatic lyrics translation has been approached by rulebased methods, statistical machine translation methods, finite-state methods with rhythmic and lexical constraints (Gervás, 2002;Manurung, 2004;He et al, 2012), and more recently by neural methods (Ghazvininejad et al, 2016(Ghazvininejad et al, , 2017(Ghazvininejad et al, , 2018. Tradi-tional song translation research has made progress in terms of lyrics translation and lyrics-melody alignment through linguistic knowledge (Haapaniemi and Laakkonen, 2019;Low, 2003Low, , 2008Low, , 2022Franzon, 2015;Desblache, 2018). Often, the object of these research was artificial songs.…”

Section: Related Workmentioning

confidence: 99%

Translate the Beauty in Songs: Jointly Learning to Align Melody and Translate Lyrics

Li¹,

Fan²,

Bu³

et al. 2023

Preprint

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Song translation requires both translation of lyrics and alignment of music notes so that the resulting verse can be sung to the accompanying melody, which is a challenging problem that has attracted some interests in different aspects of the translation process. In this paper, we propose Lyrics-Melody Translation with Adaptive Grouping (LTAG), a holistic solution to automatic song translation by jointly modeling lyrics translation and lyrics-melody alignment. It is a novel encoder-decoder framework that can simultaneously translate the source lyrics and determine the number of aligned notes at each decoding step through an adaptive note grouping module. To address data scarcity, we commissioned a small amount of training data annotated specifically for this task and used large amounts of augmented data through back-translation. Experiments conducted on an English-Chinese song translation data set show the effectiveness of our model in both automatic and human evaluations. 1

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Section: Related Workmentioning

confidence: 99%

Translate the Beauty in Songs: Jointly Learning to Align Melody and Translate Lyrics

Li¹,

Fan²,

Bu³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Automatic lyrics translation has been approached by rulebased methods, statistical machine translation methods, finite-state methods with rhythmic and lexical constraints (Gervás, 2002;Manurung, 2004;He et al, 2012), and more recently by neural methods (Ghazvininejad et al, 2016(Ghazvininejad et al, , 2017(Ghazvininejad et al, , 2018. Traditional song translation research has made progress in terms of lyrics translation and lyrics-melody alignment through linguistic knowledge (Haapaniemi and Laakkonen, 2019;Low, 2003Low, , 2008Low, , 2022Franzon, 2015;Desblache, 2018). Often, the object of these research was artificial songs.…”

Section: Related Workmentioning

confidence: 99%