@inproceedings{duriskova-etal-2024-khan,
    title = "Khan Academy Corpus: A Multilingual Corpus of Khan Academy Lectures",
    author = "{\v{D}}uri{\v{s}}kov{\'a}, Dominika  and
      Jur{\'a}{\v{s}}ov{\'a}, Daniela  and
      {\v{Z}}ilinec, Mat{\'u}{\v{s}}  and
      {\v{S}}ubert, Eduard  and
      Bojar, Ond{\v{r}}ej",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.851",
    pages = "9743--9752",
    abstract = "We present the Khan Academy Corpus totalling 10122 hours in 87394 recordings across 29 languages, where 43{\%} of recordings (4252 hours) are equipped with human-written subtitles. The subtitle texts cover a total of 137 languages. The dataset was collected from open access Khan Academy lectures, benefiting from their manual transcripts and manual translations of the transcripts. The dataset can serve in creation or evaluation of multilingual speech recognition or translation systems, featuring a diverse set of subject domains.",
}

We present the Khan Academy Corpus totalling 10122 hours in 87394 recordings across 29 languages, where 43{\%} of recordings (4252 hours) are equipped with human-written subtitles. The subtitle texts cover a total of 137 languages. The dataset was collected from open access Khan Academy lectures, benefiting from their manual transcripts and manual translations of the transcripts. The dataset can serve in creation or evaluation of multilingual speech recognition or translation systems, featuring a diverse set of subject domains.
{\v{D}}uri{\v{s}}kov{\'a}, Dominika Jur{\'a}{\v{s}}ov{\'a}, Daniela {\v{Z}}ilinec, Mat{\'u}{\v{s}} {\v{S}}ubert, Eduard Bojar, Ond{\v{r}}ej
Khan Academy Corpus: A Multilingual Corpus of Khan Academy Lectures