Song Lyrics Adaptations: Computational Interpretation of the Pentathlon Principle (2025)

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.

## introduction songs are a prominent part of human culture, everywhere in the world. since the old days, people have been singing folk songs, and adapting them to different situations. one of these adaptations is translation. rewriting a song's lyrics into another language while keeping the song singable, naturally sounding and semantically close to the original is a very complex task without a straightforward definition. @xcite defined five levels of song adaptations, ranging from leaving the song as it is, to making completely new lyrics with zero connection to the original meaning. in this paper, we are going to focus on song lyrics adaptations, while keeping both the singable aspect, as well as the semantic aspect. there have been many attempts to formalise what makes a good song translation. @xcite proposed a set of rules, called the pentathlon principle of singable translations. these guidelines are still accepted by song translators today @xcite @xcite . @xcite proposed metrics for computationally evaluating song translation quality for japanese and korean. however, to the best of our knowledge, we are the first to try to computationally interpret and verify the pentathlon principle as a whole instead of using it as a given thing. in this work, we computationally interpret @xcite in terms of collecting and proposing metrics for measuring the song translation quality. we experiment on the czech-english language pair: we collect a dataset of bilingual song lyrics and evaluate the official human-translated songs by these metrics, finding the desirable values of the metrics. as mentioned above, song lyrics translation is a difficult and complex task even for human translators. in recent years, many works try to simplify and automatize this process by using computational methods, to make translated songs more accessible. the first step of creating a singable adaptation is generating text to a given melody. many studies in generating song lyrics used datasets of melody-lyrics pairs @xcite @xcite . recently, @xcite used scansion as an intermediate step between melody and lyrics and generated chinese texts. @xcite generated lyrics to a melody without needing melody-lyrics aligned data for training. studies on automatic song translations were done mainly on chinese: @xcite fo-cused on translating lyrics for tonal languages, and @xcite used prompted machine translation with melody-based word boundaries for chinese lyrics translation. in this work, we propose an approach which explores text-to-text song lyric translation without the need for melody-aligned or bilingual training data, using generative large language models (llms). we evaluate various setups of our system using the pentathlon principle metrics, comparing the setups to the human-translated song lyrics, and through a thorough human evaluation conclude the importance of individual aspects of the pentathlon principle, and their balance. ## pentathlon principle metrics the pentathlon principle, as defined by @xcite , consists of five aspects of lyrics. it states that all these aspects should be balanced, the same as an athlete competing in a pentathlon has to have balanced skills in all five activities to be successful. the five aspects of singable translations are singability, sense, naturalness, rhyme and rhythm. in this section, we discuss each aspect of the pentathlon principle from the computational point of view. we present five metrics, each measuring one aspect of the pentathlon principle. 1 first, let us introduce the notation used for the metric descriptions. all proposed metrics are section-wise, giving scores for each section (e.g. verse or chorus) separately. the pentathlon principle was proposed in the context of singable translations, so most of the metrics have the sourcelanguage lyrics and the targe-language lyrics as inputs. we denote the source-language lyrics section consisting of n lines as @xmath0, . . . , x n } and the translated target-language lyrics section as @xmath1, . . . , xn }. @xcite describes singability as the comfort of the lyrics being sung to a certain melody. while singability is closely tied with stress patterns and line lengths, low addresses these under the term rhythm, as do we. singability encompasses the adequateness of certain syllables being placed at certain parts of the song. @xcite emphasises consonant clusters and vowel openness as key parts of singability, explaining that large consonant clusters and tight syllables are awkaward to sing if the melody is not adapted to it. ## lyrics generation system while previous approaches to song lyrics adaptation were through machine translation, song lyric adaptation using generative llms is underexplored. in this section, we propose a text-totext song lyrics generation system based on the pentathlon principle. this system can be trained using only the target language data, and when provided with lyrics in a source language, it produces a singable adaptation of the lyrics in a target language. our pipeline (see figure 1 ) has several steps, each described in more detail in the following subsections. the pipeline input is the lyrics of a song section in the source language, divided into individual lines. the output is lyrics in the target language that are singable to the same melody as the input lyrics, while also retaining similar meaning, naturalness, rhythm and rhyme. first, defining features of the source lyrics are extracted (section 3.1). then, a prompt for an llm is built based on the extracted features of the source lyrics (section 3.2). based on this prompt, a fine-tuned llm generates the lyrics in the target language. the training process of the model is described in section 3.3 and the inference process is described in section 3.4. finally, the generated lyrics are post-processed (section 3.5). ## experimental setup for @xmath2 we tested everything on an english-czech language pair, in the direction of english to czech. we describe the @xmath3.1, the implementation details of the pentathlon principle metrics and the feature extraction function specific for czech and english in section 4.2, and in section 4.3 we discuss the llm selection, training and inference. ## evaluation and discussion in this section, we evaluate our experimental setup on the test part of the parallel dataset introduced in section 4.1.1. we use the english song lyrics as the source for all the following evaluations. as the target language song sections, we are using the official czech translations from the parallel data in section 5.2, machine translations (mt) foot_7 of the english lyrics into czech in section 5.3 and data generated by the lyrics generating system from section 3 in section 5.4. we also evaluate a random baseline in section 5.1. all of the above-mentioned evaluations are automatic, using the pentathlon principle metrics. the results can be seen in in section 5.5, we present a manual evaluation of the various czech song lyrics adaptations, paired with statistics about human preference of individual pentathlon principle metrics and the dependencies of these preferences on choices in the evaluation. ## conclusion in this work, we propose an automatic metric system based on the pentathlon principle: metrics measuring the singability, sense, naturalness, rhyme and rhythm of translated song lyrics, and measure the ideal values of the metrics on human-translated official song lyrics. we propose a lyric translation system based on the pentathlon principle and implement it for the english-czech language pair. we use the proposed metrics and human evaluation to compare the official translations, our generated translations and machine translations. the evaluation shows the validity of both our metrics and our lyric translation approach, as well as some insight into human preference when it comes to song translations, confirming low's pentathlon principle.