| # JamendoLyrics MultiLang dataset for lyrics research | |
| A dataset containing 80 songs with different genres and languages along with lyrics that | |
| are time-aligned on a word-by-word level (with start and end times) to the music. | |
| To cite this dataset and for more information, please refer to the following paper, where this | |
| dataset was first used: | |
| [Similarity-based Audio-Lyrics Alignment of Multiple Languages | |
| ](https://arxiv.org/abs/2306.07744) | |
| \ | |
| [ICASSP 2023](https://ieeexplore.ieee.org/document/10096725) | |
| \ | |
| Simon Durand, Daniel Stoller, Sebastian Ewert | |
| ## Installation | |
| The dataset can be used without installation by cloning it from this Github repository. | |
| For running any of the included scripts, we require Python 3.10 with packages installed as | |
| listed in ``requirements.txt.`` | |
| ## Metadata CSV | |
| All songs are listed in `JamendoLyrics.csv` together with their metadata. | |
| To load annotations you are interested in, you can iterate over this CSV and use the `Filepath` | |
| column to build file paths to files containing the data for each song (audio file, lyrics | |
| annotations). Among the metadata, "LyricOverlap" refers to whether or not the lyrics in the song overlap, | |
| “Polyphonic” refers to whether or not there are multiple singers singing the same lyrics, but with different melodies, | |
| and "NonLexical" refers to whether or not there is non-lexical singing (eg: scatting). | |
| ## Lyrics files | |
| In the `lyrics` subfolder, we provide the lyrics to each song as `SONG_NAME.txt` (normalized, e. | |
| g. special characters and characters not supported in `vocab/international.characters` are removed) | |
| Furthermore, `SONG_NAME.words.txt` contains all the words, separated by | |
| lines, ignoring the paragraph structure of the original lyrics. This is used for the word-level timestamp annotations. | |
| ## Time-aligned lyrics annotations | |
| We have aligned the lyrics on a word-by-word and line-by-line basis to the music. | |
| Word-by-word start and end timestamps are stored in the "annotations/words" subfolder, and they | |
| also indicate whether the word represents the end of a line as well (it will have the word end | |
| timestamp set instead of NaN). | |
| A line-by-line version of the lyrics is stored in the subfolder | |
| "annotations/lines" as CSV files, denoting the start and end time of each lyrical line in the audio. | |
| These contain one row per line in the form of `(start_time, end_time, lyrics_line)` and can be | |
| used to train or evaluate models only on a line-by-line level. | |
| ### Modifying word-by-word timestamps | |
| In case the word timestamps are modified, one needs to run `generate_lines.py` to | |
| update the line-level timestamp files in "annotations/lines" accordingly. | |
| This is because the line-level annotation in "annotations/lines" is auto-generated based on the manual | |
| word-by-word annotations: The start timestamp for each line is set to be the start timestamp of the | |
| word after an end-of-line word. | |
| In case you find errors in the timestamp annotations, we encourage you to submit a pull request | |
| to this repository so we can correct the errors. | |
| ## Acknowledgements | |
| We want to acknowledge our 2022 Research intern, [Emir Demirel](https://emirdemirel.github.io/), | |
| and Torr Yatco for their help in assembling this dataset. | |
| ## Original dataset | |
| This dataset is an extended version of the original JamendoLyrics dataset presented in the paper | |
| [End-to-end Lyrics Alignment for Polyphonic Music Using an Audio-to-Character Recognition Model](https://arxiv.org/abs/1902.06797) | |
| It originally contained only 20 English songs and is now deprecated as annotations are slightly improved, | |
| so we discourage its use in the future. | |
| You can find it archived [here](https://github.com/f90/jamendolyrics/releases/tag/original). | |