Datasets:
task_categories:
- automatic-speech-recognition
language:
- en
- fr
- de
- es
tags:
- music
- lyrics
- evaluation
- benchmark
- transcription
pretty_name: 'JamALT: A Formatting-Aware Lyrics Transcription Benchmark'
JamALT: A Formatting-Aware Lyrics Transcription Benchmark
JamALT is a revision of the JamendoLyrics dataset (80 songs in 4 languages), adapted for use as an automatic lyrics transcription (ALT) benchmark.
The lyrics have been revised according to the newly compiled annotation guidelines, which include rules about spelling, punctuation, and formatting.
The audio is identical to the JamendoLyrics dataset.
However, only 79 songs are included, as one of the 20 French songs (La_Fin_des_Temps_-_BuzzBonBon) has been removed due to concerns about potentially harmful content.
See the project website for details.
Loading the data
from datasets import load_dataset
dataset = load_dataset("audioshake/jam-alt")["test"]
A subset is defined for each language (en, fr, de, es);
for example, use load_dataset("audioshake/jam-alt", "es") to load only the Spanish songs.
Other arguments can be specified to control audio loading:
with_audio=Falseto skip loading audio.sampling_rateandmono=Trueto control the sampling rate and number of channels.decode_audio=Falseto skip decoding the audio and just get the MP3 file paths.
Running evaluation
Use the alt-eval package for evaluation:
from alt_eval import compute_metrics
compute_metrics(dataset["text"], transcriptions, languages=dataset["language"])