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Kamel Smaili

Kamel Smaili has 4 papers in our library, in 2015–2025, most of them on Semitic languages, Machine translation, Language models & pretraining; often with David Langlois, Karima Meftouh, Salima Harrat.

4 papers in our library · 2015–2025

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📄 4 works in our library · 🔗 Cited 71 times in our library · ⭐ Paper Stars ranking: #5954

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Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksPsychology · 1 workExperimental and Cognitive Psychology · 1 workSignal Processing · 1 work

🧭 Topics 4Research subjects and languages the work is about.Semitic languages · 4 worksMachine translation · 1 workSpeech & spoken language · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20251 paper

2010s

20191 paper20171 paper20151 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Machine Translation Experiments on PADIC: A Parallel Arabic DIalect Corpus (2015 · 132 citations)
    Arabic dialects are mostly spoken, lack standard spelling, and have few written resources. This makes data-driven translation between them and Modern Standard Arabic (MSA) difficult. The authors address this gap with PADIC, a multi-dialect parallel corpus created manually rather than harvested from the web, because…
  2. An enhanced automatic speech recognition system for Arabic (2017 · 24 citations)
    Arabic speech recognition is hard for several reasons. The morphology is rich, so many words fall outside the vocabulary. Written text usually omits short vowels, so one written form can have many pronunciations. The hamoza sign is often confused or left out. The authors build a Modern Standard Arabic (MSA)…
  3. The SMarT Classifier for Arabic Fine-Grained Dialect Identification (2019 · 14 citations)
    The paper describes the SMarT group's entry to subtask 1 of the MADAR shared task. The task was to identify, at the sentence level, which of 25 Arab city dialects or Modern Standard Arabic a sentence is written in. The authors trained only on the official Corpus-26 and Corpus-6 data. Two neural options, an LSTM and a…
  4. ABDUL: A New Approach to Build Language Models for Dialects Using Formal Language Corpora Only (2025 · 1 citation)
    North African Arabic dialects (Moroccan, Algerian, Tunisian) have little training data, no standard orthography, and many loanwords.

 Co-authors here

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 71 times (of the 149,439 papers whose bibliographies we read); 49 citing papers with a page here →.

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