@article{alharbi-etal-2026-saudi,
    title = "Saudi {ASWAT}: A Large-Scale Corpus of Spontaneous Saudi {A}rabic Speech",
    author = "Alharbi, Abdullah I.  and
      Altamimi, Afrah A.  and
      Alhoshan, Muneera  and
      Almazrua, Amal  and
      Alharbi, Halah Munif  and
      Almuqhim, Bayan M.  and
      Aljasim, Hawra  and
      Alosaimy, Abdulrahman  and
      Asiri, Yahya A.  and
      Alfaifi, Abdullah",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.124/",
    pages = "1595--1602",
    abstract = "Spontaneous Arabic speech is scarce in current corpora, and it is not well represented. This poses a limitation invisibility of spontaneous Arabic to automatic speech recognition (ASR), speaker diarization, and sociolinguistic research. The Saudi ASWAT project fills a major gap by creating the first nationwide corpus of natural Saudi speech, where data has been recorded and transcribed under a systematic methodology and ecologically valid conditions. The corpus aims to collect 2,500 hours of natural conversations from a diverse range of participants. These has been selected from five major Saudi regional varieties, Najdi (Central), Eastern, Hijazi (Western), Northern, and Southern, covering more than fifty five local varieties. Speech has been recorded by trained fieldworkers using participants own devices to reflect real-life variation. The annotated data incorporate a variety of speaker demographics, regional vocabularies which differ from the standard lexicon, and structured metadata. TF{--}IDF profiling shows regional differences in a range of performing words. Data also represent balanced age and gender sampling to support studies of intergenerational and sociophonetic variation. Saudi ASWAT provides the most linguistically diverse resources of Saudi Arabia to date. Additionally, it establishes an ethical governed framework for Arabic speech data creation to enable advances in both computational modeling and linguistic research."
}