@inproceedings{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",
booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resource Association",
url = "https://aclanthology.org/2026.lrec-1.124/",
doi = "10.63317/5dmcn5u57hg6",
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."
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<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.</abstract>
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%0 Conference Proceedings
%T Saudi ASWAT: A Large-Scale Corpus of Spontaneous Saudi Arabic Speech
%A Alharbi, Abdullah I.
%A Altamimi, Afrah A.
%A Alhoshan, Muneera
%A Almazrua, Amal
%A Alharbi, Halah Munif
%A Almuqhim, Bayan M.
%A Aljasim, Hawra
%A Alosaimy, Abdulrahman
%A Asiri, Yahya A.
%A Alfaifi, Abdullah
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F alharbi-etal-2026-saudi
%X 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.
%R 10.63317/5dmcn5u57hg6
%U https://aclanthology.org/2026.lrec-1.124/
%U https://doi.org/10.63317/5dmcn5u57hg6
%P 1595-1602
Markdown (Informal)
[Saudi ASWAT: A Large-Scale Corpus of Spontaneous Saudi Arabic Speech](https://aclanthology.org/2026.lrec-1.124/) (Alharbi et al., LREC 2026)
ACL
- Abdullah I. Alharbi, Afrah A. Altamimi, Muneera Alhoshan, Amal Almazrua, Halah Munif Alharbi, Bayan M. Almuqhim, Hawra Aljasim, Abdulrahman Alosaimy, Yahya A. Asiri, and Abdullah Alfaifi. 2026. Saudi ASWAT: A Large-Scale Corpus of Spontaneous Saudi Arabic Speech. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 1595–1602, Palma de Mallorca, Spain. ELRA Language Resource Association.