Masader: Metadata Sourcing for Arabic Text and Speech Data Resources

Zaid Alyafeai; Maraim Masoud; Mustafa Ghaleb; Maged S. Al-Shaibani

Masader: Metadata Sourcing for Arabic Text and Speech Data Resources

Zaid Alyafeai
, Maraim Masoud
, Mustafa Ghaleb
, Maged S. Al-Shaibani

Interdisciplinary Research Center for Intelligent Secure Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

The NLP pipeline has evolved dramatically in the last few years. The first step in the pipeline is to find suitable annotated datasets to evaluate the tasks we are trying to solve. Unfortunately, most of the published datasets lack metadata annotations that describe their attributes. Not to mention, the absence of a public catalogue that indexes all the publicly available datasets related to specific regions or languages. When we consider low-resource dialectical languages, for example, this issue becomes more prominent. In this paper, we create Masader, the largest public catalogue for Arabic NLP datasets, which consists of 200 datasets annotated with 25 attributes. Furthermore, we develop a metadata annotation strategy that could be extended to other languages. We also make remarks and highlight some issues about the current status of Arabic NLP datasets and suggest recommendations to address them.

Original language	English
Title of host publication	2022 Language Resources and Evaluation Conference, LREC 2022
Editors	Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
Publisher	European Language Resources Association (ELRA)
Pages	6340-6351
Number of pages	12
ISBN (Electronic)	9791095546726
State	Published - 2022
Event	13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France Duration: 20 Jun 2022 → 25 Jun 2022

Publication series

Name	2022 Language Resources and Evaluation Conference, LREC 2022

Conference

Conference	13th International Conference on Language Resources and Evaluation Conference, LREC 2022
Country/Territory	France
City	Marseille
Period	20/06/22 → 25/06/22

Bibliographical note

Publisher Copyright:
© European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

Keywords

LR Infrastructures and Architectures
Less-Resourced
Metadata

ASJC Scopus subject areas

Language and Linguistics
Library and Information Sciences
Linguistics and Language
Education

Cite this

Alyafeai, Z., Masoud, M., Ghaleb, M., & Al-Shaibani, M. S. (2022). Masader: Metadata Sourcing for Arabic Text and Speech Data Resources. In N. Calzolari, F. Bechet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, J. Odijk, & S. Piperidis (Eds.), 2022 Language Resources and Evaluation Conference, LREC 2022 (pp. 6340-6351). (2022 Language Resources and Evaluation Conference, LREC 2022). European Language Resources Association (ELRA).

Alyafeai, Zaid ; Masoud, Maraim ; Ghaleb, Mustafa et al. / Masader : Metadata Sourcing for Arabic Text and Speech Data Resources. 2022 Language Resources and Evaluation Conference, LREC 2022. editor / Nicoletta Calzolari ; Frederic Bechet ; Philippe Blache ; Khalid Choukri ; Christopher Cieri ; Thierry Declerck ; Sara Goggi ; Hitoshi Isahara ; Bente Maegaard ; Joseph Mariani ; Helene Mazo ; Jan Odijk ; Stelios Piperidis. European Language Resources Association (ELRA), 2022. pp. 6340-6351 (2022 Language Resources and Evaluation Conference, LREC 2022).

@inproceedings{f3389dd4fd144880b21d3d8bac2cafab,

title = "Masader: Metadata Sourcing for Arabic Text and Speech Data Resources",

abstract = "The NLP pipeline has evolved dramatically in the last few years. The first step in the pipeline is to find suitable annotated datasets to evaluate the tasks we are trying to solve. Unfortunately, most of the published datasets lack metadata annotations that describe their attributes. Not to mention, the absence of a public catalogue that indexes all the publicly available datasets related to specific regions or languages. When we consider low-resource dialectical languages, for example, this issue becomes more prominent. In this paper, we create Masader, the largest public catalogue for Arabic NLP datasets, which consists of 200 datasets annotated with 25 attributes. Furthermore, we develop a metadata annotation strategy that could be extended to other languages. We also make remarks and highlight some issues about the current status of Arabic NLP datasets and suggest recommendations to address them.",

keywords = "LR Infrastructures and Architectures, Less-Resourced, Metadata",

author = "Zaid Alyafeai and Maraim Masoud and Mustafa Ghaleb and Al-Shaibani, \{Maged S.\}",

note = "Publisher Copyright: {\textcopyright} European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.; 13th International Conference on Language Resources and Evaluation Conference, LREC 2022 ; Conference date: 20-06-2022 Through 25-06-2022",

year = "2022",

language = "English",

series = "2022 Language Resources and Evaluation Conference, LREC 2022",

publisher = "European Language Resources Association (ELRA)",

pages = "6340--6351",

editor = "Nicoletta Calzolari and Frederic Bechet and Philippe Blache and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Helene Mazo and Jan Odijk and Stelios Piperidis",

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Alyafeai, Z, Masoud, M, Ghaleb, M & Al-Shaibani, MS 2022, Masader: Metadata Sourcing for Arabic Text and Speech Data Resources. in N Calzolari, F Bechet, P Blache, K Choukri, C Cieri, T Declerck, S Goggi, H Isahara, B Maegaard, J Mariani, H Mazo, J Odijk & S Piperidis (eds), 2022 Language Resources and Evaluation Conference, LREC 2022. 2022 Language Resources and Evaluation Conference, LREC 2022, European Language Resources Association (ELRA), pp. 6340-6351, 13th International Conference on Language Resources and Evaluation Conference, LREC 2022, Marseille, France, 20/06/22.

Masader: Metadata Sourcing for Arabic Text and Speech Data Resources. / Alyafeai, Zaid; Masoud, Maraim; Ghaleb, Mustafa et al.
2022 Language Resources and Evaluation Conference, LREC 2022. ed. / Nicoletta Calzolari; Frederic Bechet; Philippe Blache; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Helene Mazo; Jan Odijk; Stelios Piperidis. European Language Resources Association (ELRA), 2022. p. 6340-6351 (2022 Language Resources and Evaluation Conference, LREC 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Masader

T2 - 13th International Conference on Language Resources and Evaluation Conference, LREC 2022

AU - Alyafeai, Zaid

AU - Masoud, Maraim

AU - Ghaleb, Mustafa

AU - Al-Shaibani, Maged S.

N1 - Publisher Copyright: © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

PY - 2022

Y1 - 2022

N2 - The NLP pipeline has evolved dramatically in the last few years. The first step in the pipeline is to find suitable annotated datasets to evaluate the tasks we are trying to solve. Unfortunately, most of the published datasets lack metadata annotations that describe their attributes. Not to mention, the absence of a public catalogue that indexes all the publicly available datasets related to specific regions or languages. When we consider low-resource dialectical languages, for example, this issue becomes more prominent. In this paper, we create Masader, the largest public catalogue for Arabic NLP datasets, which consists of 200 datasets annotated with 25 attributes. Furthermore, we develop a metadata annotation strategy that could be extended to other languages. We also make remarks and highlight some issues about the current status of Arabic NLP datasets and suggest recommendations to address them.

AB - The NLP pipeline has evolved dramatically in the last few years. The first step in the pipeline is to find suitable annotated datasets to evaluate the tasks we are trying to solve. Unfortunately, most of the published datasets lack metadata annotations that describe their attributes. Not to mention, the absence of a public catalogue that indexes all the publicly available datasets related to specific regions or languages. When we consider low-resource dialectical languages, for example, this issue becomes more prominent. In this paper, we create Masader, the largest public catalogue for Arabic NLP datasets, which consists of 200 datasets annotated with 25 attributes. Furthermore, we develop a metadata annotation strategy that could be extended to other languages. We also make remarks and highlight some issues about the current status of Arabic NLP datasets and suggest recommendations to address them.

KW - LR Infrastructures and Architectures

KW - Less-Resourced

KW - Metadata

UR - https://www.scopus.com/pages/publications/85141306872

M3 - Conference contribution

AN - SCOPUS:85141306872

T3 - 2022 Language Resources and Evaluation Conference, LREC 2022

SP - 6340

EP - 6351

BT - 2022 Language Resources and Evaluation Conference, LREC 2022

A2 - Calzolari, Nicoletta

A2 - Bechet, Frederic

A2 - Blache, Philippe

A2 - Choukri, Khalid

A2 - Cieri, Christopher

A2 - Declerck, Thierry

A2 - Goggi, Sara

A2 - Isahara, Hitoshi

A2 - Maegaard, Bente

A2 - Mariani, Joseph

A2 - Mazo, Helene

A2 - Odijk, Jan

A2 - Piperidis, Stelios

PB - European Language Resources Association (ELRA)

Y2 - 20 June 2022 through 25 June 2022

ER -

Alyafeai Z, Masoud M, Ghaleb M, Al-Shaibani MS. Masader: Metadata Sourcing for Arabic Text and Speech Data Resources. In Calzolari N, Bechet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Odijk J, Piperidis S, editors, 2022 Language Resources and Evaluation Conference, LREC 2022. European Language Resources Association (ELRA). 2022. p. 6340-6351. (2022 Language Resources and Evaluation Conference, LREC 2022).

Masader: Metadata Sourcing for Arabic Text and Speech Data Resources

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

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Cite this