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MANorm: A Normalization Dictionary for Moroccan Arabic Dialect Written in Latin Script

arXiv 2206.09167 ↗First posted 18 Jun 2022cs.CLcited by 0

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Abstract (arXiv)

Social media user-generated text is actually the main resource for many NLP tasks. This text however, does not follow the standard rules of writing. Moreover, the use of dialect such as Moroccan Arabic in written communications increases further NLP tasks complexity. A dialect is a verbal language that does not have a standard orthography, which leads users to improvise spelling while writing. Thus, for the same word we can find multiple forms of transliterations. Subsequently, it is mandatory to normalize these different transliterations to one canonical word form. To reach this goal, we have exploited the powerfulness of word embedding models generated with a corpus of YouTube comments. Besides, using a Moroccan Arabic dialect dictionary that provides the canonical forms, we have built a normalization dictionary that we refer to as MANorm. We have conducted several experiments to demonstrate the efficiency of MANorm, which have shown its usefulness in dialect normalization.

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References · 5

  1. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  2. 2016Enriching Word Vectors with Subword Informationcited by 1,583
  3. 2018Universal Dependency Parsing for Hindi-English Code-switchingcited by 18
  4. 2017MoNoise: Modeling Noise Using a Modular Normalization Systemcited by 8
  5. 2017Exploring Word Embeddings for Unsupervised Textual User-Generated Content Normalizationcited by 4

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