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    <abstract>The success of machine learning for automatic speech processing has raised the need for large scale datasets. However, collecting such data is often a challenging task as it implies significant investment involving time and money cost. In this paper, we devise a recipe for building largescale Speech Corpora by harnessing Web resources namely YouTube, other Social Media, Online Radio and TV. We illustrate our methodology by building KALAM’DZ, An Arabic Spoken corpus dedicated to Algerian dialectal varieties. The preliminary version of our dataset covers all major Algerian dialects. In addition, we make sure that this material takes into account numerous aspects that foster its richness. In fact, we have targeted various speech topics. Some automatic and manual annotations are provided. They gather useful information related to the speakers and sub-dialect information at the utterance level. Our corpus encompasses the 8 major Algerian Arabic sub-dialects with 4881 speakers and more than 104.4 hours segmented in utterances of at least 6 s.</abstract>
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%0 Conference Proceedings
%T Toward a Web-based Speech Corpus for Algerian Dialectal Arabic Varieties
%A Bougrine, Soumia
%A Chorana, Aicha
%A Lakhdari, Abdallah
%A Cherroun, Hadda
%Y Habash, Nizar
%Y Diab, Mona
%Y Darwish, Kareem
%Y El-Hajj, Wassim
%Y Al-Khalifa, Hend
%Y Bouamor, Houda
%Y Tomeh, Nadi
%Y El-Haj, Mahmoud
%Y Zaghouani, Wajdi
%S Proceedings of the Third Arabic Natural Language Processing Workshop
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F bougrine-etal-2017-toward
%X The success of machine learning for automatic speech processing has raised the need for large scale datasets. However, collecting such data is often a challenging task as it implies significant investment involving time and money cost. In this paper, we devise a recipe for building largescale Speech Corpora by harnessing Web resources namely YouTube, other Social Media, Online Radio and TV. We illustrate our methodology by building KALAM’DZ, An Arabic Spoken corpus dedicated to Algerian dialectal varieties. The preliminary version of our dataset covers all major Algerian dialects. In addition, we make sure that this material takes into account numerous aspects that foster its richness. In fact, we have targeted various speech topics. Some automatic and manual annotations are provided. They gather useful information related to the speakers and sub-dialect information at the utterance level. Our corpus encompasses the 8 major Algerian Arabic sub-dialects with 4881 speakers and more than 104.4 hours segmented in utterances of at least 6 s.
%R 10.18653/v1/W17-1317
%U https://aclanthology.org/W17-1317
%U https://doi.org/10.18653/v1/W17-1317
%P 138-146

Markdown (Informal)

[Toward a Web-based Speech Corpus for Algerian Dialectal Arabic Varieties](https://aclanthology.org/W17-1317) (Bougrine et al., WANLP 2017)

• Toward a Web-based Speech Corpus for Algerian Dialectal Arabic Varieties (Bougrine et al., WANLP 2017)

ACL

• Soumia Bougrine, Aicha Chorana, Abdallah Lakhdari, and Hadda Cherroun. 2017. Toward a Web-based Speech Corpus for Algerian Dialectal Arabic Varieties. In Proceedings of the Third Arabic Natural Language Processing Workshop, pages 138–146, Valencia, Spain. Association for Computational Linguistics.