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Arabizi vs LLMs: Can the Genie Understand the Language of Aladdin?
Computation and Language · Submitted 28 Feb 2025
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Arabizi is widely used on social media and allows people to communicate in an informal and dynamic way, but it poses significant challenges for machine translation due to its lack of formal structure and deeply embedded cultural nuances.
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.
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The abstract, sentence by sentence
In this era of rapid technological advancements, communication continues to evolve as new linguistic phenomena emerge. Among these is Arabizi, a hybrid form of Arabic that incorporates Latin characters and numbers to represent the spoken dialects of Arab communities. Arabizi is widely used on social media and allows people to communicate in an informal and dynamic way, but it poses significant challenges for machine translation due to its lack of formal structure and deeply embedded cultural nuances. This case study arises from a growing need to translate Arabizi for gisting purposes. It evaluates the capacity of different LLMs to decode and translate Arabizi, focusing on multiple Arabic dialects that have rarely been studied up until now. Using a combination of human evaluators and automatic metrics, this research project investigates the model's performance in translating Arabizi into both Modern Standard Arabic and English. Key questions explored include which dialects are translated most effectively and whether translations into English surpass those into Arabic.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | In this era of rapid technological advancements, communication continues to evolve as new linguistic phenomena emerge. | background 1.00 | 0.03 | 0.01 | asserted 1.00 |
| s1 | Among these is Arabizi, a hybrid form of Arabic that incorporates Latin characters and numbers to represent the spoken dialects of Arab communities. | background 1.00 | 0.04 | 0.02 | asserted 1.00 |
| s2 | Arabizi is widely used on social media and allows people to communicate in an informal and dynamic way, but it poses significant challenges for machine translation due to its lack of formal structure and deeply embedded cultural nuances. | background 0.98 | 0.06 | 0.04 | asserted 1.00 |
| s3 | This case study arises from a growing need to translate Arabizi for gisting purposes. | background 0.76 | 0.13 | 0.02 | asserted 0.99 |
| s4 | It evaluates the capacity of different LLMs to decode and translate Arabizi, focusing on multiple Arabic dialects that have rarely been studied up until now. | contribution 0.99 | 0.81 | 0.04 | asserted 0.97 |
| s5 | Using a combination of human evaluators and automatic metrics, this research project investigates the model's performance in translating Arabizi into both Modern Standard Arabic and English. | method 0.99 | 0.93 | 0.03 | asserted 0.98 |
| s6 | Key questions explored include which dialects are translated most effectively and whether translations into English surpass those into Arabic. | contribution 0.88 | 0.46 | 0.03 | unclear 0.87 |
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The paper
Original abstract
In this era of rapid technological advancements, communication continues to evolve as new linguistic phenomena emerge. Among these is Arabizi, a hybrid form of Arabic that incorporates Latin characters and numbers to represent the spoken dialects of Arab communities. Arabizi is widely used on social media and allows people to communicate in an informal and dynamic way, but it poses significant challenges for machine translation due to its lack of formal structure and deeply embedded cultural nuances. This case study arises from a growing need to translate Arabizi for gisting purposes. It evaluates the capacity of different LLMs to decode and translate Arabizi, focusing on multiple Arabic dialects that have rarely been studied up until now. Using a combination of human evaluators and automatic metrics, this research project investigates the model's performance in translating Arabizi into both Modern Standard Arabic and English. Key questions explored include which dialects are translated most effectively and whether translations into English surpass those into Arabic.
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What this paper does with the arXiv papers it cites
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All scores were calculated using SacreBLEU [ref] .[The relevant signatures are provided in Appendix [ref].] In order to avoid the usual pitfalls of word- and character-based metrics, especially since we were studying dialects without formal orthography, we further investigated the quality of the translations using techniques based on sub-word embeddings: BERTScore [ref] and two versions of COMET: COMET-22 [ref] and its reference-free version CometKiwi [ref] .
BERTScore: Evaluating Text Generation with BERT · Automatic Evaluation · 1.00
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