---
title: "Arabic Dialect Identification — Zaidan 2014"
description: "Arabic text is dominated by Modern Standard Arabic (MSA), the standardized written variety."
authors: ["Omar F. Zaidan", "Chris Callison-Burch"]
year: 2014
venue: "Computational Linguistics"
source: "https://aclanthology.org/J14-1006/"
doi: "10.1162/coli_a_00169"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/zaidan-2014-arabic-dialect-identification/"
---
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# Arabic Dialect Identification

**Authors:** [Omar F. Zaidan](https://md.research.elamur.ai/free/en/authors/omar-f-zaidan/), [Chris Callison-Burch](https://md.research.elamur.ai/free/en/authors/chris-callison-burch/) · **Year:** 2014 · **Venue:** Computational Linguistics · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/J14-1006/) · [PDF](https://aclanthology.org/J14-1006.pdf) · [DOI 10.1162/coli\_a\_00169](https://doi.org/10.1162/coli_a_00169) · [OpenAlex](https://openalex.org/W2160802179)

**Citations:** 294 citations (openalex-snapshot · 2026-10-14) · [142](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary

Arabic text is dominated by Modern Standard Arabic (MSA), the standardized written variety. The regional dialects that people actually speak are rarely written and poorly covered by existing corpora. Because all varieties share one script and much vocabulary, telling them apart automatically is difficult. The authors address this by building a dialect-rich resource from reader comments posted on Arabic online newspapers, the Arabic Online Commentary Data set (AOC). Through Amazon's Mechanical Turk, they gathered sentence-level labels for over 100,000 sentences, marking how dialectal each sentence is and which dialect it uses. The labels also reveal annotator biases, such as people over-attributing sentences to their own dialect. For classification, they train a separate language model for each Arabic variety and assign a sentence to the model that scores it best. These dialect-trained models clearly beat baselines built on much larger MSA-only data and come close to human accuracy. The resource and classifiers make it possible to collect dialectal text at scale for NLP tasks such as machine translation.

## Key points

- **Resource:** the Arabic Online Commentary Data set (AOC), built from newspaper reader commentary, with crowdsourced dialect annotation for more than 100,000 sentences.
- **Method:** each sentence is scored with n-gram language models trained separately per Arabic variety.
- **Main result:** on one task, the system reached 85.7% accuracy, compared with 88.0% for human annotators and only 66.6% for an MSA-only baseline.
- **Annotator behavior:** workers tended to over-identify their own dialect.
- **Application:** the classifiers were run on a Web crawl of 3.5 million pages from online Arabic newspapers to find dialectal content. Future work proposes morphological features (e.g., from BAMA, MAGEAD, ADAM, CALIMA) and covering more dialects.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/)

## Cited by

Cited by

142 papers of our library cite it (of the 140673 whose bibliographies we read); 27 of them have a page here, 115 not yet.

- [Arabic Dialect Classification using RNNs, Transformers, and Large Language Models: A Comparative Analysis](https://md.research.elamur.ai/free/en/papers/a-2025-essameldin-arabic-dialect-classification-using-rnns/)
- [Arabic Dialect Identification in the Wild](https://md.research.elamur.ai/free/en/papers/abdelali-2020-arabic-dialect-identification-wild/)
- [ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic](https://md.research.elamur.ai/free/en/papers/abdul-2021-mageed-arbert-marbert-deep-bidirectional-transformers/)
- [A Neural Architecture for Dialectal Arabic Segmentation](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-samih-neural-architecture-dialectal-arabic-segmentation/)
- [DialectalArabicMMLU: Benchmarking Dialectal Capabilities in Arabic and Multilingual Language Models](https://md.research.elamur.ai/free/en/papers/altakrori-2026-dialectalarabicmmlu-benchmarking-dialectal-capabilities-arabic/)
- [Automatic Arabic Dialect Identification Systems for Written Texts: A Survey](https://md.research.elamur.ai/free/en/papers/althobaiti-2020-automatic-arabic-dialect-identification-systems/)
- [Hierarchical Aggregation of Dialectal Data for Arabic Dialect Identification](https://md.research.elamur.ai/free/en/papers/baimukan-2022-hierarchical-aggregation-dialectal-data-arabic/)
- [ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets](https://md.research.elamur.ai/free/en/papers/baly-2019-arsentd-lev-multi-topic-corpus/)
- [A Multidialectal Parallel Corpus of Arabic](https://md.research.elamur.ai/free/en/papers/bouamor-2014-multidialectal-parallel-corpus-arabic/)
- [The MADAR Shared Task on Arabic Fine-Grained Dialect Identification](https://md.research.elamur.ai/free/en/papers/bouamor-2019-madar-shared-task-arabic-fine/)
- [Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation](https://md.research.elamur.ai/free/en/papers/esmaeil-2026-rosetta-alexandriax-2026-lora-adapted/)
- [On the importance of Data Scale in Pretraining Arabic Language Models](https://md.research.elamur.ai/free/en/papers/ghaddar-2024-importance-data-scale-pretraining-arabic/)
- [Arabic natural language processing: An overview](https://md.research.elamur.ai/free/en/papers/guellil-2019-arabic-natural-language-processing-overview/)
- [Habibi - a multi Dialect multi National Arabic Song Lyrics Corpus](https://md.research.elamur.ai/free/en/papers/haj-2020-habibi-multi-dialect-multi-national/)
- [Automatic Language Identification in Texts: A Survey](https://md.research.elamur.ai/free/en/papers/jauhiainen-2019-automatic-language-identification-texts/)
- [Exploring Data and Parameter Efficient Strategies for Arabic Dialect Identifications](https://md.research.elamur.ai/free/en/papers/kanjirangat-2025-exploring-data-parameter-efficient-strategies/)
- [Learning the Arabic Dialect Continuum as a Continuous Space: A Regression Approach to Speaker Origin Prediction](https://md.research.elamur.ai/free/en/papers/khadraoui-2026-learning-arabic-dialect-continuum-continuous/)
- [Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM](https://md.research.elamur.ai/free/en/papers/langstream-2017-eldesouki-arabic-multi-dialect-segmentation-bi/)
- [Discriminating between Similar Languages and Arabic Dialect Identification: A Report on the Third DSL Shared Task](https://md.research.elamur.ai/free/en/papers/malmasi-2016-discriminating-between-similar-languages/)
- [BERT-based Multi-Task Model for Country and Province Level Modern Standard Arabic and Dialectal Arabic Identification](https://md.research.elamur.ai/free/en/papers/mekki-2021-bert-based-multi-task-model-country/)
- [ASOS at NADI 2024 shared task: Bridging Dialectness Estimation and MSA Machine Translation for Arabic Language Enhancement](https://md.research.elamur.ai/free/en/papers/nacar-2024-asos-nadi-2024-shared-task/)
- [AraT5: Text-to-Text Transformers for Arabic Language Generation](https://md.research.elamur.ai/free/en/papers/nagoudi-2022-arat5-text-text-transformers-arabic/)
- [A Parameter-Efficient Learning Approach to Arabic Dialect Identification with Pre-Trained General-Purpose Speech Model](https://md.research.elamur.ai/free/en/papers/radhakrishnan-2023-parameter-efficient-learning-approach-arabic/)
- [Fine-Grained Arabic Dialect Identification](https://md.research.elamur.ai/free/en/papers/salameh-2018-fine-grained-arabic-dialect-identification/)
- [Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic](https://md.research.elamur.ai/free/en/papers/sarkar-2022-parameter-data-efficient-continual-pre/)
- [Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual Data](https://md.research.elamur.ai/free/en/papers/schuler-2026-dialectal-filtering-synthesizing-kurdish-corpora/)
- [A Report on the DSL Shared Task 2014](https://md.research.elamur.ai/free/en/papers/zampieri-2014-report-dsl-shared-task/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@article{zaidan2014arabic,
  title = {{Arabic Dialect Identification}},
  author = {Zaidan, Omar F. and Callison-Burch, Chris},
  journal = {Computational Linguistics},
  year = {2014},
  doi = {10.1162/coli\_a\_00169},
  url = {https://doi.org/10.1162/coli_a_00169}
}
```

- [← previous Annotation as a New Paradigm in Research Archiving](https://md.research.elamur.ai/free/en/papers/langstream-2014-roorda-annotation-new-paradigm-research-archiving/)
- [next → Augmenting FrameNet Via PPDB](https://md.research.elamur.ai/free/en/papers/rastogi-2014-augmenting-framenet-ppdb/)
- [↑ back to papers of 2014](https://md.research.elamur.ai/free/en/papers/2014/)

## References

49 references, 8 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Abdel-Massih, Ernest T., Zaki N. Abdel-Malek, and El-Said M. Badawi. 1979. A Reference Grammar of Egyptian Arabic. Georgetown University Press. [find](https://scholar.google.com/scholar?q=Abdel%2DMassih%2C+Ernest+T%2E%2C+Zaki+N%2E+Abdel%2DMalek%2C+and+El%2DSaid+M%2E+Badawi%2E+1979%2E+A+Reference+Grammar+of+Egyptian+Arabic%2E+Georgetown+University+Press%2E)
2. Al-Ani, Salman H. 1970. Arabic Phonology: An Acoustical and Physiological Investigation. Mouton. [find](https://scholar.google.com/scholar?q=Al%2DAni%2C+Salman+H%2E+1970%2E+Arabic+Phonology%3A+An+Acoustical+and+Physiological+Investigation%2E+Mouton%2E)
3. Aoun, Joseph, Elabbas Benmamoun, and Dominique Sportiche. 1994. Agreement, word order, and conjunction in some varieties of Arabic. Linguistic Inquiry, 25(2):195–220. [find](https://scholar.google.com/scholar?q=Aoun%2C+Joseph%2C+Elabbas+Benmamoun%2C+and+Dominique+Sportiche%2E+1994%2E+Agreement%2C+word+order%2C+and+conjunction+in+some+varieties+of+Arabic%2E+Linguistic+Inquiry%2C+25%282%29%3A195%E2%80%93220%2E)
4. Badawi, El-Said and Martin Hinds. 1986. A Dictionary of Egyptian Arabic. Librairie du Liban. [find](https://scholar.google.com/scholar?q=Badawi%2C+El%2DSaid+and+Martin+Hinds%2E+1986%2E+A+Dictionary+of+Egyptian+Arabic%2E+Librairie+du+Liban%2E)
5. Bassiouney, Reem. 2009. Arabic Sociolinguistics. Edinburgh University Press. [find](https://scholar.google.com/scholar?q=Bassiouney%2C+Reem%2E+2009%2E+Arabic+Sociolinguistics%2E+Edinburgh+University+Press%2E)
6. Biadsy, Fadi, Julia Hirschberg, and Nizar Habash. 2009. Spoken Arabic dialect identification using phonotactic modeling. In Proceedings of the EACL Workshop on Computational Approaches to Semitic Languages, pages 53–61, Athens. [find](https://scholar.google.com/scholar?q=Biadsy%2C+Fadi%2C+Julia+Hirschberg%2C+and+Nizar+Habash%2E+2009%2E+Spoken+Arabic+dialect+identification+using+phonotactic+modeling%2E+In+Proceedings+of+the+EACL+Workshop+on+Computational+Approaches+to+Semitic+Lang)
7. Buckwalter, Tim. 2002. Buckwalter Arabic transliteration. [http://www.qamus.org/transliteration.htm](http://www.qamus.org/transliteration.htm). [↗](http://www.qamus.org/transliteration.htm)
8. Buckwalter, Tim. 2004. Buckwalter Arabic morphological analyzer version 2.0. Linguistic Data Consortium, Philadelphia, PA. [↗](https://doi.org/10.35111/050q-5r95)
9. Callison-Burch, Chris and Mark Dredze. 2010. Creating speech and language data with Amazon’s Mechanical Turk. In Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk, pages 1–12, Los Angeles, CA. [find](https://scholar.google.com/scholar?q=Callison%2DBurch%2C+Chris+and+Mark+Dredze%2E+2010%2E+Creating+speech+and+language+data+with+Amazon%E2%80%99s+Mechanical+Turk%2E+In+Proceedings+of+the+NAACL+HLT+2010+Workshop+on+Creating+Speech+and+Language+Data+with+Am)
10. Cavnar, William B. and John M. Trenkle. 1994. N-gram-based text categorization. In Proceedings of SDAIR-94, pages 161–175, Vilnius. [find](https://scholar.google.com/scholar?q=Cavnar%2C+William+B%2E+and+John+M%2E+Trenkle%2E+1994%2E+N%2Dgram%2Dbased+text+categorization%2E+In+Proceedings+of+SDAIR%2D94%2C+pages+161%E2%80%93175%2C+Vilnius%2E)
11. Chen, Stanley F. and Joshua T. Goodman. 1998. An empirical study of smoothing techniques for language modeling. Technical Report TR-10-98, Computer Science Group, Harvard University. [↗](https://doi.org/10.1006/csla.1999.0128) [our card](https://md.research.elamur.ai/free/en/papers/chen-1996-empirical-study-smoothing-techniques-language/)
12. Chiang, David, Mona Diab, Nizar Habash, Owen Rambow, and Safiullah Shareef. 2006. Parsing Arabic dialects. In Proceedings of EACL, pages 369–376, Trento. [↗](https://doi.org/10.7916/d85t3tzg) [our card](https://md.research.elamur.ai/free/en/papers/aclbulk-2006-chiang-parsing-arabic-dialects/)
13. Cowell, Mark W. 1964. A Reference Grammar of Syrian Arabic. Georgetown University Press. [find](https://scholar.google.com/scholar?q=Cowell%2C+Mark+W%2E+1964%2E+A+Reference+Grammar+of+Syrian+Arabic%2E+Georgetown+University+Press%2E)
14. Diab, Mona, Nizar Habash, Owen Rambow, Mohamed Altantawy, and Yassine Benajiba. 2010. COLABA: Arabic dialect annotation and processing. In Proceedings of the LREC Workshop on Semitic Language Processing, pages 66–74. [find](https://scholar.google.com/scholar?q=Diab%2C+Mona%2C+Nizar+Habash%2C+Owen+Rambow%2C+Mohamed+Altantawy%2C+and+Yassine+Benajiba%2E+2010%2E+COLABA%3A+Arabic+dialect+annotation+and+processing%2E+In+Proceedings+of+the+LREC+Workshop+on+Semitic+Language+Processi)
15. Dunning, T. 1994. Statistical identification of language. Technical Report MCCS 94-273, New Mexico State University. [find](https://scholar.google.com/scholar?q=Dunning%2C+T%2E+1994%2E+Statistical+identification+of+language%2E+Technical+Report+MCCS+94%2D273%2C+New+Mexico+State+University%2E)
16. Erwin, Wallace. 1963. A Short Reference Grammar of Iraqi Arabic. Georgetown University Press. [find](https://scholar.google.com/scholar?q=Erwin%2C+Wallace%2E+1963%2E+A+Short+Reference+Grammar+of+Iraqi+Arabic%2E+Georgetown+University+Press%2E)
17. Fleiss, Joseph L. 1971. Measuring nominal scale agreement among many raters. Psychological Bulletin, 76(5):378–382. [↗](https://doi.org/10.1037/h0031619)
18. Gairdner, William Henry Temple. 1925. The Phonetics of Arabic. Oxford University Press. [find](https://scholar.google.com/scholar?q=Gairdner%2C+William+Henry+Temple%2E+1925%2E+The+Phonetics+of+Arabic%2E+Oxford+University+Press%2E)
19. Garera, Nikesh and David Yarowsky. 2009. Modeling latent biographic attributes in conversational genres. In Proceedings of ACL, pages 710–718, Singapore. [find](https://scholar.google.com/scholar?q=Garera%2C+Nikesh+and+David+Yarowsky%2E+2009%2E+Modeling+latent+biographic+attributes+in+conversational+genres%2E+In+Proceedings+of+ACL%2C+pages+710%E2%80%93718%2C+Singapore%2E)
20. Habash, Nizar. 2008. Four techniques for online handling of out-of-vocabulary words in Arabic-English statistical machine translation. In Proceedings of ACL, Short Papers, pages 57–60, Columbus, OH. [find](https://scholar.google.com/scholar?q=Habash%2C+Nizar%2E+2008%2E+Four+techniques+for+online+handling+of+out%2Dof%2Dvocabulary+words+in+Arabic%2DEnglish+statistical+machine+translation%2E+In+Proceedings+of+ACL%2C+Short+Papers%2C+pages+57%E2%80%9360%2C+Columbus%2C+OH%2E)
21. Habash, Nizar, Mona Diab, and Owen Rambow. 2012. Conventional orthography for dialectal Arabic. In Proceedings of the Language Resources and Evaluation Conference (LREC), pages 711–718, Istanbul. [find](https://scholar.google.com/scholar?q=Habash%2C+Nizar%2C+Mona+Diab%2C+and+Owen+Rambow%2E+2012%2E+Conventional+orthography+for+dialectal+Arabic%2E+In+Proceedings+of+the+Language+Resources+and+Evaluation+Conference+%28LREC%29%2C+pages+711%E2%80%93718%2C+Istanbul%2E) [our card](https://md.research.elamur.ai/free/en/papers/habash-2012-conventional-orthography-dialectal-arabic/)
22. Habash, Nizar, Ramy Eskander, and Abdelati Hawwari. 2012. A morphological analyzer for Egyptian Arabic. In Proceedings of the Twelfth Meeting of the Special Interest Group on Computational Morphology and Phonology, pages 1–9, Montréal. [find](https://scholar.google.com/scholar?q=Habash%2C+Nizar%2C+Ramy+Eskander%2C+and+Abdelati+Hawwari%2E+2012%2E+A+morphological+analyzer+for+Egyptian+Arabic%2E+In+Proceedings+of+the+Twelfth+Meeting+of+the+Special+Interest+Group+on+Computational+Morphology+) [our card](https://md.research.elamur.ai/free/en/papers/lingbulk-2012-habash-morphological-analyzer-egyptian-arabic/)
23. Habash, Nizar and Owen Rambow. 2006. MAGEAD: A morphological analyzer and generator for the Arabic dialects. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, pages 681–688, Sydney. [↗](https://doi.org/10.7916/d87s7x73) [our card](https://md.research.elamur.ai/free/en/papers/aclbulk-2006-habash-magead-morphological-analyzer-generator-arabic/)
24. Habash, Nizar, Owen Rambow, Mona Diab, and Reem Kanjawi-Faraj. 2008. Guidelines for annotation of Arabic dialectness. In Proceedings of the LREC Workshop on HLT & NLP within the Arabic World, pages 49–53, Marrakech. [find](https://scholar.google.com/scholar?q=Habash%2C+Nizar%2C+Owen+Rambow%2C+Mona+Diab%2C+and+Reem+Kanjawi%2DFaraj%2E+2008%2E+Guidelines+for+annotation+of+Arabic+dialectness%2E+In+Proceedings+of+the+LREC+Workshop+on+HLT+%26+NLP+within+the+Arabic+World%2C+pages+49)
25. Habash, Nizar, Abdelhadi Soudi, and Tim Buckwalter. 2007. On Arabic transliteration. In Antal van den Bosch, Abdelhadi Soudi, and Günter Neumann, editors, Arabic Computational Morphology: Knowledge-based and Empirical Methods. Kluwer/Springer Publications, chapter 2. [↗](https://doi.org/10.1007/978-1-4020-6046-5_2)
26. Habash, Nizar Y. 2010. Introduction to Arabic Natural Language Processing. Morgan & Claypool. [↗](https://doi.org/10.1007/978-3-031-02139-8)
27. Haeri, Niloofar. 2003. Sacred Language, Ordinary People: Dilemmas of Culture and Politics in Egypt. Palgrave Macmillan. [find](https://scholar.google.com/scholar?q=Haeri%2C+Niloofar%2E+2003%2E+Sacred+Language%2C+Ordinary+People%3A+Dilemmas+of+Culture+and+Politics+in+Egypt%2E+Palgrave+Macmillan%2E)
28. Holes, Clive. 2004. Modern Arabic: Structures, Functions, and Varieties. Georgetown Classics in Arabic Language and Linguistics. Georgetown University Press. [find](https://scholar.google.com/scholar?q=Holes%2C+Clive%2E+2004%2E+Modern+Arabic%3A+Structures%2C+Functions%2C+and+Varieties%2E+Georgetown+Classics+in+Arabic+Language+and+Linguistics%2E+Georgetown+University+Press%2E)
29. Ingham, Bruce. 1994. Najdi Arabic: Central Arabian. John Benjamins. [find](https://scholar.google.com/scholar?q=Ingham%2C+Bruce%2E+1994%2E+Najdi+Arabic%3A+Central+Arabian%2E+John+Benjamins%2E)
30. Kästner, Hartmut. 1981. Phonetik und Phonologie des modernen Hocharabisch. Verlag Enzyklopädie. [find](https://scholar.google.com/scholar?q=Ka%CC%88stner%2C+Hartmut%2E+1981%2E+Phonetik+und+Phonologie+des+modernen+Hocharabisch%2E+Verlag+Enzyklopa%CC%88die%2E)
31. Landis, J. Richard and Gary G. Koch. 1977. The measurement of observer agreement for categorical data. Biometrics, 33:159–174. [↗](https://doi.org/10.2307/2529310)
32. Lei, Yun and John H. L. Hansen. 2011. Dialect classification via text-independent training and testing for Arabic, Spanish, and Chinese. IEEE Transactions on Audio, Speech, and Language Processing, 19(1):85–96. [↗](https://doi.org/10.1109/tasl.2010.2045184)
33. Mitchell, Terence Frederick. 1990. Pronouncing Arabic. Clarendon Press. [find](https://scholar.google.com/scholar?q=Mitchell%2C+Terence+Frederick%2E+1990%2E+Pronouncing+Arabic%2E+Clarendon+Press%2E)
34. Mohand, Tilmatine. 1999. Substrat et convergences: Le berbére et l’arabe nord-africain. Estudios de Dialectologiá Norteaafricana y andalusı́, 4:99–119. [find](https://scholar.google.com/scholar?q=Mohand%2C+Tilmatine%2E+1999%2E+Substrat+et+convergences%3A+Le+berbe%CC%81re+et+l%E2%80%99arabe+nord%2Dafricain%2E+Estudios+de+Dialectologia%CC%81+Norteaafricana+y+andalus%C4%B1%CC%81%2C+4%3A99%E2%80%93119%2E)
35. Newman, Daniel L. 2002. The phonetic status of Arabic within the world’s languages. Antwerp Papers in Linguistics, 100:63–75. [find](https://scholar.google.com/scholar?q=Newman%2C+Daniel+L%2E+2002%2E+The+phonetic+status+of+Arabic+within+the+world%E2%80%99s+languages%2E+Antwerp+Papers+in+Linguistics%2C+100%3A63%E2%80%9375%2E)
36. Novotney, Scott, Rich Schwartz, and Sanjeev Khudanpur. 2011. Unsupervised Arabic dialect adaptation with self-training. In Interspeech, pages 541–544, Florence. [find](https://scholar.google.com/scholar?q=Novotney%2C+Scott%2C+Rich+Schwartz%2C+and+Sanjeev+Khudanpur%2E+2011%2E+Unsupervised+Arabic+dialect+adaptation+with+self%2Dtraining%2E+In+Interspeech%2C+pages+541%E2%80%93544%2C+Florence%2E)
37. Řehůřek, Radim and Milan Kolkus. 2009. Language Identification on the Web: Extending the Dictionary Method, volume 5449 of Lecture Notes in Computer Science, pages 357–368. SpringerLink. [find](https://scholar.google.com/scholar?q=R%CC%8Cehu%CC%8Ar%CC%8Cek%2C+Radim+and+Milan+Kolkus%2E+2009%2E+Language+Identification+on+the+Web%3A+Extending+the+Dictionary+Method%2C+volume+5449+of+Lecture+Notes+in+Computer+Science%2C+pages+357%E2%80%93368%2E+SpringerLink%2E)
38. Salloum, Wael and Nizar Habash. 2011. Dialectal to standard Arabic paraphrasing to improve Arabic-English statistical machine translation. In Proceedings of the EMNLP Workshop on Algorithms and Resources for Modelling of Dialects and Language Varieties, pages 10–21, Edinburgh. [↗](https://doi.org/10.7916/d8697bg2)
39. Shlonsky, Ur. 1997. Clause Structure and Word Order in Hebrew and Arabic: An Essay in Comparative Semitic Syntax. Oxford University Press. [find](https://scholar.google.com/scholar?q=Shlonsky%2C+Ur%2E+1997%2E+Clause+Structure+and+Word+Order+in+Hebrew+and+Arabic%3A+An+Essay+in+Comparative+Semitic+Syntax%2E+Oxford+University+Press%2E)
40. Souter, Clive, Gavin Churcher, Judith Hayes, John Hughes, and Stephen Johnson. 1994. Natural language identification using corpus-based models. Hermes Journal of Linguistics, 13:183–203. [find](https://scholar.google.com/scholar?q=Souter%2C+Clive%2C+Gavin+Churcher%2C+Judith+Hayes%2C+John+Hughes%2C+and+Stephen+Johnson%2E+1994%2E+Natural+language+identification+using+corpus%2Dbased+models%2E+Hermes+Journal+of+Linguistics%2C+13%3A183%E2%80%93203%2E)
41. Suleiman, Yasir. 1994. Nationalism and the Arabic language: A historical overview. In Yasir Suleiman, editor, Arabic Sociolinguistics. Curzon Press. [find](https://scholar.google.com/scholar?q=Suleiman%2C+Yasir%2E+1994%2E+Nationalism+and+the+Arabic+language%3A+A+historical+overview%2E+In+Yasir+Suleiman%2C+editor%2C+Arabic+Sociolinguistics%2E+Curzon+Press%2E)
42. Thelwall, Robin and M. Akram Sa’Adeddin. 1990. Arabic. Journal of the International Phonetic Association, 20(2):37–39. [find](https://scholar.google.com/scholar?q=Thelwall%2C+Robin+and+M%2E+Akram+Sa%E2%80%99Adeddin%2E+1990%2E+Arabic%2E+Journal+of+the+International+Phonetic+Association%2C+20%282%29%3A37%E2%80%9339%2E)
43. Verma, Brijesh, Hong Lee, and John Zakos. 2009. An Automatic Intelligent Language Classifier, volume 5507 of Lecture Notes in Computer Science, pages 639–646. SpringerLink. [find](https://scholar.google.com/scholar?q=Verma%2C+Brijesh%2C+Hong+Lee%2C+and+John+Zakos%2E+2009%2E+An+Automatic+Intelligent+Language+Classifier%2C+volume+5507+of+Lecture+Notes+in+Computer+Science%2C+pages+639%E2%80%93646%2E+SpringerLink%2E)
44. Versteegh, Kees. 2001. The Arabic Language. Edinburgh University Press. [find](https://scholar.google.com/scholar?q=Versteegh%2C+Kees%2E+2001%2E+The+Arabic+Language%2E+Edinburgh+University+Press%2E)
45. Zaidan, Omar, Jason Eisner, and Christine Piatko. 2007. Using “annotator rationales” to improve machine learning for text categorization. In Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference, pages 260–267, Rochester, NY. [find](https://scholar.google.com/scholar?q=Zaidan%2C+Omar%2C+Jason+Eisner%2C+and+Christine+Piatko%2E+2007%2E+Using+%E2%80%9Cannotator+rationales%E2%80%9D+to+improve+machine+learning+for+text+categorization%2E+In+Human+Language+Technologies+2007%3A+The+Conference+of+the+Nor) [our card](https://md.research.elamur.ai/free/en/papers/zaidan-2007-annotator-rationales-improve-machine-learning/)
46. Zaidan, Omar F. 2012. Crowdsourcing Annotation for Machine Learning in Natural Language Processing Tasks. Ph.D. thesis, Johns Hopkins University, Baltimore, MD. [find](https://scholar.google.com/scholar?q=Zaidan%2C+Omar+F%2E+2012%2E+Crowdsourcing+Annotation+for+Machine+Learning+in+Natural+Language+Processing+Tasks%2E+Ph%2ED%2E+thesis%2C+Johns+Hopkins+University%2C+Baltimore%2C+MD%2E)
47. Zaidan, Omar F. and Chris Callison-Burch. 2011. The Arabic Online Commentary Dataset: An annotated dataset of informal Arabic with high dialectal content. In Proceedings of ACL, pages 37–41, Portland, OR. [find](https://scholar.google.com/scholar?q=Zaidan%2C+Omar+F%2E+and+Chris+Callison%2DBurch%2E+2011%2E+The+Arabic+Online+Commentary+Dataset%3A+An+annotated+dataset+of+informal+Arabic+with+high+dialectal+content%2E+In+Proceedings+of+ACL%2C+pages+37%E2%80%9341%2C+Portland%2C) [our card](https://md.research.elamur.ai/free/en/papers/zaidan-2011-arabic-online-commentary-dataset-annotated/)
48. Zbib, Rabih, Erika Malchiodi, Jacob Devlin, David Stallard, Spyros Matsoukas, Richard Schwartz, John Makhoul, Omar F. Zaidan, and Chris Callison-Burch. 2012. Machine translation of Arabic dialects. In the 2012 Conference of the North American Chapter of the Association for Computational Linguistics, pages 49–59, Montreal. [find](https://scholar.google.com/scholar?q=Zbib%2C+Rabih%2C+Erika+Malchiodi%2C+Jacob+Devlin%2C+David+Stallard%2C+Spyros+Matsoukas%2C+Richard+Schwartz%2C+John+Makhoul%2C+Omar+F%2E+Zaidan%2C+and+Chris+Callison%2DBurch%2E+2012%2E+Machine+translation+of+Arabic+dialects%2E+In) [our card](https://md.research.elamur.ai/free/en/papers/zbib-2012-machine-translation-arabic-dialects/)
49. Zissman, Marc A. 1996. Comparison of four approaches to automatic language identification of telephone speech. IEEE Transactions on Speech and Audio Processing, 4(1):31–44. [↗](https://doi.org/10.1109/tsa.1996.481450)