Results 101 to 110 of about 5,167 (235)

Exploiting Dialect Identification in Automatic Dialectal Text Normalization [PDF]

open access: yesarXiv
Dialectal Arabic is the primary spoken language used by native Arabic speakers in daily communication. The rise of social media platforms has notably expanded its use as a written language. However, Arabic dialects do not have standard orthographies.
arxiv  

Place as a Metaphysical Problem in Albert the Great and Thomas Aquinas

open access: yesModern Theology, Volume 41, Issue 2, Page 292-310, April 2025.
Abstract Thomas Aquinas’ particular synthesis of Aristotelianism and Neoplatonism, and the intellectual tradition it inaugurated, has at least twice faced critical challenges from developments in physics. Besieged by the sixteenth and seventeenth century novatores and more or less ignored by the nineteenth‐ and twentieth‐century practitioners of ...
Onsi Aaron Kamel
wiley   +1 more source

al Lahjaat fii al Lughoh al ‘Arabiyah (Dirosah Tahliliyah ‘an Asbaab Ikhtilaaf al Lahjaat wa ‘Anaashiriha)

open access: yesJurnal Al Bayan: Jurnal Jurusan Pendidikan Bahasa Arab, 2018
ABSTRAK Dialect, according to many Arabic linguists, refers to language and letters used by a particular community that cause differences in the pronunciation even in the way particular letters are used among different societies.
Muflihah muflihah
doaj   +1 more source

TRAPPED BETWEEN CASE AND NUMBER. A TYPOLOGY OF ADNUMERATIVE FORMS†

open access: yesStudia Linguistica, Volume 79, Issue 1, Page 215-257, April 2025.
In this paper, I study the nature of adnumerative or numerative forms; i.e. morphologically dedicated inflectional forms that can only be used with numerals or quantifiers (e.g. Russian dva časá ‘two o'clock’ vs. [gen sg] čása). Adnumeratives are cross‐linguistically very rare; yet they raise some interesting theoretical discussions. This work is based
Kristian Roncero
wiley   +1 more source

Romanized Tunisian dialect transliteration using sequence labelling techniques

open access: yesJournal of King Saud University: Computer and Information Sciences, 2022
In recent years, social web users in Arabic countries have been resorting to the dialects as a written language in their social exchanges. Arabic dialects derive from modern standard Arabic (MSA) and differ significantly from one country to another and ...
Jihene Younes   +3 more
doaj  

Open Universal Arabic ASR Leaderboard [PDF]

open access: yesarXiv
In recent years, the enhanced capabilities of ASR models and the emergence of multi-dialect datasets have increasingly pushed Arabic ASR model development toward an all-dialect-in-one direction. This trend highlights the need for benchmarking studies that evaluate model performance on multiple dialects, providing the community with insights into models'
arxiv  

The role of Saudi universities in facilitating the understanding of national dialects A critical statistical study

open access: yesمجلة العلوم التربوية والدراسات الإنسانية سلسلة الآداب والعلوم التربوية والإنسانية والتطبيقية
This study explores the role of Saudi universities in helping non-Arabic speakers understand national dialects. A descriptive analytical approach was used, focusing on a random sample of students learning Arabic as a second language.
Jawhara Al Asmari   +5 more
doaj   +1 more source

Estimating the Level of Dialectness Predicts Interannotator Agreement in Multi-dialect Arabic Datasets [PDF]

open access: yesarXiv
On annotating multi-dialect Arabic datasets, it is common to randomly assign the samples across a pool of native Arabic speakers. Recent analyses recommended routing dialectal samples to native speakers of their respective dialects to build higher-quality datasets. However, automatically identifying the dialect of samples is hard. Moreover, the pool of
arxiv  

AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs [PDF]

open access: yesarXiv
Arabic, with its rich diversity of dialects, remains significantly underrepresented in Large Language Models, particularly in dialectal variations. We address this gap by introducing seven synthetic datasets in dialects alongside Modern Standard Arabic (MSA), created using Machine Translation (MT) combined with human post-editing.
arxiv  

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