# Songs Across Borders: Singable and Controllable Neural Lyric Translation

arXiv: https://arxiv.org/abs/2305.16816 · HTML: https://mlsanity.com/paper/2305.16816/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 41 references that are in the map.
- First posted on arXiv 26 May 2023.

## Builds on (most cited first, 20 of 20)

- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [Multilingual Denoising Pre-training for Neural Machine Translation](https://mlsanity.com/paper/2001.08210/) (2020)
- [Improving Neural Machine Translation Models with Monolingual Data](https://mlsanity.com/paper/1511.06709/) (2015)
- [Multilingual Translation with Extensible Multilingual Pretraining and Finetuning](https://mlsanity.com/paper/2008.00401/) (2020)
- [Unsupervised Machine Translation Using Monolingual Corpora Only](https://mlsanity.com/paper/1711.00043/) (2017)
- [Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search](https://mlsanity.com/paper/1704.07138/) (2017)
- [Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation](https://mlsanity.com/paper/1804.06609/) (2018)
- [Unsupervised Neural Machine Translation](https://mlsanity.com/paper/1710.11041/) (2017)
- [Hybrid Spectrogram and Waveform Source Separation](https://mlsanity.com/paper/2111.03600/) (2021)
- [Lexically Constrained Neural Machine Translation with Levenshtein Transformer](https://mlsanity.com/paper/2004.12681/) (2020)
- [Controlling the Output Length of Neural Machine Translation](https://mlsanity.com/paper/1910.10408/) (2019)
- [SongNet: Rigid Formats Controlled Text Generation](https://mlsanity.com/paper/2004.08022/) (2020)
- [DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling](https://mlsanity.com/paper/2107.01875/) (2021)
- [PoeLM: A Meter- and Rhyme-Controllable Language Model for Unsupervised Poetry Generation](https://mlsanity.com/paper/2205.12206/) (2022)
- [Iterative Domain-Repaired Back-Translation](https://mlsanity.com/paper/2010.02473/) (2020)
- [On the Generation of Medical Dialogues for COVID-19](https://mlsanity.com/paper/2005.05442/) (2020)
- [Automatic Song Translation for Tonal Languages](https://mlsanity.com/paper/2203.13420/) (2022)
- [Integrating Vectorized Lexical Constraints for Neural Machine Translation](https://mlsanity.com/paper/2203.12210/) (2022)
- [Input Augmentation Improves Constrained Beam Search for Neural Machine Translation: NTT at WAT 2021](https://mlsanity.com/paper/2106.05450/) (2021)

## Built on by (most cited first, 11 of 11)

- [Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://mlsanity.com/paper/2406.03930/) (2024)
- [SwiLTra-Bench: The Swiss Legal Translation Benchmark](https://mlsanity.com/paper/2503.01372/) (2025)
- [A Computational Evaluation Framework for Singable Lyric Translation](https://mlsanity.com/paper/2308.13715/) (2023)
- [K-pop Lyric Translation: Dataset, Analysis, and Neural-Modelling](https://mlsanity.com/paper/2309.11093/) (2023)
- [Isolating Culture Neurons in Multilingual Large Language Models](https://mlsanity.com/paper/2508.02241/) (2025)
- [REFFLY: Melody-Constrained Lyrics Editing Model](https://mlsanity.com/paper/2409.00292/) (2024)
- [Sing it, Narrate it: Quality Musical Lyrics Translation](https://mlsanity.com/paper/2410.22066/) (2024)
- [Joint Learning of Wording and Formatting for Singable Melody-to-Lyric Generation](https://mlsanity.com/paper/2307.02146/) (2023)
- [LyriCAR: A Difficulty-Aware Curriculum Reinforcement Learning Framework For Controllable Lyric Translation](https://mlsanity.com/paper/2510.19967/) (2025)
- [HOMURA: Taming the Sand-Glass for Time-Constrained LLM Translation via Reinforcement Learning](https://mlsanity.com/paper/2601.10187/) (2026)
- [MAVL: A Multilingual Audio-Video Lyrics Dataset for Animated Song Translation](https://mlsanity.com/paper/2505.18614/) (2025)

## Abstract (arXiv)

The development of general-domain neural machine translation (NMT) methods has advanced significantly in recent years, but the lack of naturalness and musical constraints in the outputs makes them unable to produce singable lyric translations. This paper bridges the singability quality gap by formalizing lyric translation into a constrained translation problem, converting theoretical guidance and practical techniques from translatology literature to prompt-driven NMT approaches, exploring better adaptation methods, and instantiating them to an English-Chinese lyric translation system. Our model achieves 99.85%, 99.00%, and 95.52% on length accuracy, rhyme accuracy, and word boundary recall. In our subjective evaluation, our model shows a 75% relative enhancement on overall quality, compared against naive fine-tuning (Code available at https://github.com/Sonata165/ControllableLyricTranslation).