@inproceedings{stepankova-rosa-2025-song,
title = "Song Lyrics Adaptations: Computational Interpretation of the Pentathlon Principle",
author = "{\v{S}}t{\v{e}}p{\'a}nkov{\'a}, Barbora and
Rosa, Rudolf",
editor = {H{\"a}m{\"a}l{\"a}inen, Mika and
{\"O}hman, Emily and
Bizzoni, Yuri and
Miyagawa, So and
Alnajjar, Khalid},
booktitle = "Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities",
month = may,
year = "2025",
address = "Albuquerque, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.nlp4dh-1.11/",
doi = "10.18653/v1/2025.nlp4dh-1.11",
pages = "117--128",
ISBN = "979-8-89176-234-3",
abstract = "Songs are an integral part of human culture, and they often resonate the most when we can sing them in our native language. However, translating song lyrics presents a unique challenge: maintaining singability, naturalness, and semantic fidelity. In this work, we computationally interpret Low{'}s Pentathlon Principle of singable translations to be able to properly measure the quality of adapted lyrics, breaking it down into five measurable metrics that reflect the key aspects of singable translations. Building on this foundation, we introduce a text-to-text song lyrics translation system based on generative large language models, designed to meet the Pentathlon Principle{'}s criteria, without relying on melodies or bilingual training data.We experiment on the English-Czech language pair: we collect a dataset of English-to-Czech bilingual song lyrics and identify the desirable values of the five Pentathlon Principle metrics based on the values achieved by human translators. Through detailed human assessment of automatically generated lyric translations, we confirm the appropriateness of the proposed metrics as well as the general validity of the Pentathlon Principle, with some insights into the variation in people{'}s individual preferences. All code and data are available at https://github.com/stepankovab/Computational-Interpretation-of-the-Pentathlon-Principle."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="stepankova-rosa-2025-song">
<titleInfo>
<title>Song Lyrics Adaptations: Computational Interpretation of the Pentathlon Principle</title>
</titleInfo>
<name type="personal">
<namePart type="given">Barbora</namePart>
<namePart type="family">Štěpánková</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rudolf</namePart>
<namePart type="family">Rosa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities</title>
</titleInfo>
<name type="personal">
<namePart type="given">Mika</namePart>
<namePart type="family">Hämäläinen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Emily</namePart>
<namePart type="family">Öhman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Yuri</namePart>
<namePart type="family">Bizzoni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">So</namePart>
<namePart type="family">Miyagawa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Khalid</namePart>
<namePart type="family">Alnajjar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Albuquerque, USA</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-234-3</identifier>
</relatedItem>
<abstract>Songs are an integral part of human culture, and they often resonate the most when we can sing them in our native language. However, translating song lyrics presents a unique challenge: maintaining singability, naturalness, and semantic fidelity. In this work, we computationally interpret Low’s Pentathlon Principle of singable translations to be able to properly measure the quality of adapted lyrics, breaking it down into five measurable metrics that reflect the key aspects of singable translations. Building on this foundation, we introduce a text-to-text song lyrics translation system based on generative large language models, designed to meet the Pentathlon Principle’s criteria, without relying on melodies or bilingual training data.We experiment on the English-Czech language pair: we collect a dataset of English-to-Czech bilingual song lyrics and identify the desirable values of the five Pentathlon Principle metrics based on the values achieved by human translators. Through detailed human assessment of automatically generated lyric translations, we confirm the appropriateness of the proposed metrics as well as the general validity of the Pentathlon Principle, with some insights into the variation in people’s individual preferences. All code and data are available at https://github.com/stepankovab/Computational-Interpretation-of-the-Pentathlon-Principle.</abstract>
<identifier type="citekey">stepankova-rosa-2025-song</identifier>
<identifier type="doi">10.18653/v1/2025.nlp4dh-1.11</identifier>
<location>
<url>https://aclanthology.org/2025.nlp4dh-1.11/</url>
</location>
<part>
<date>2025-05</date>
<extent unit="page">
<start>117</start>
<end>128</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Song Lyrics Adaptations: Computational Interpretation of the Pentathlon Principle
%A Štěpánková, Barbora
%A Rosa, Rudolf
%Y Hämäläinen, Mika
%Y Öhman, Emily
%Y Bizzoni, Yuri
%Y Miyagawa, So
%Y Alnajjar, Khalid
%S Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, USA
%@ 979-8-89176-234-3
%F stepankova-rosa-2025-song
%X Songs are an integral part of human culture, and they often resonate the most when we can sing them in our native language. However, translating song lyrics presents a unique challenge: maintaining singability, naturalness, and semantic fidelity. In this work, we computationally interpret Low’s Pentathlon Principle of singable translations to be able to properly measure the quality of adapted lyrics, breaking it down into five measurable metrics that reflect the key aspects of singable translations. Building on this foundation, we introduce a text-to-text song lyrics translation system based on generative large language models, designed to meet the Pentathlon Principle’s criteria, without relying on melodies or bilingual training data.We experiment on the English-Czech language pair: we collect a dataset of English-to-Czech bilingual song lyrics and identify the desirable values of the five Pentathlon Principle metrics based on the values achieved by human translators. Through detailed human assessment of automatically generated lyric translations, we confirm the appropriateness of the proposed metrics as well as the general validity of the Pentathlon Principle, with some insights into the variation in people’s individual preferences. All code and data are available at https://github.com/stepankovab/Computational-Interpretation-of-the-Pentathlon-Principle.
%R 10.18653/v1/2025.nlp4dh-1.11
%U https://aclanthology.org/2025.nlp4dh-1.11/
%U https://doi.org/10.18653/v1/2025.nlp4dh-1.11
%P 117-128
Markdown (Informal)
[Song Lyrics Adaptations: Computational Interpretation of the Pentathlon Principle](https://aclanthology.org/2025.nlp4dh-1.11/) (Štěpánková & Rosa, NLP4DH 2025)
ACL