Language & Culture

How Many Countries Speak Arabic Around the World?

History of the Arabic Language

Arabic is one of the famous languages that have wide global popularity. It is part of the Central Semitic language family which includes Aramaic, Hebrew, and Phoenician. The Arabic language is believed to have evolved from Aramaic more than a millennium ago among the Bedouin nomadic tribes in the deserts of the Arabian peninsula.

In the 7th century, Arabic spread with the Islamic conquests which extended across the Middle East, North Africa, Central and Western Asia, and even it parts of China. The native Arab’s presence along with their language, religion, and culture on the other side of the world played a huge role in planting a seed for Arabic to sprout for centuries to come.

Nowadays, all Arabic speakers have their own native colloquial variety, reaching up to 30 different dialects. However, Modern Standard Arabic – which is the universal pluricentric variety preferred in the media, the workplace, professional translation, and the law – remains the only Arabic taught across all levels of education. All literary texts authored between the seventh and ninth centuries, as well as the Holy Quran, are written in Classical Arabic.

Arabic Speaking Countries Map

The majority of Arabic speaking countries are concentrated in the Arabian Peninsula, the Middle East, and North Africa, which is known as “The Arab World”. However, there are around 25 Arab speaking countries that claim Arabic as an official or co-official language including Saudi Arabia, Chad, Algeria, Comoros, Eritrea, Djibouti, Egypt, Palestine, Lebanon, Iraq, Jordan, Lebanon, Kuwait, Mauritania, Morocco, Oman, Qatar, Somalia, Sudan, Syria, Tanzania, Bahrain, Tunisia, United Arab Emirates, and Yemen. Meanwhile, there are six sovereign states where Arabic is a national language or “recognized minority language” such as Turkey, Niger, Iran, Senegal, and Mali.

Today, Arabic is spreading once more outside the premises of its geographic concentration as more Arabic speakers migrate and settle all over the world, with generations after generations of Arabic speaking expats continue to live in Southeast Asia, Brazil, Europe, Canda, and the United States of America.

For a more detailed overview of the Arabic Speaking countries, check the table below:

Countries where Arabic is an Official Language

No	Country	Population	No. of Arabic Speakers
1	Egypt	100,000,000	82,449,200
2	Algeria	41,701,000	40,100,000
3	Sudan	40,235,000	28,164,500
4	Iraq	36,004,552	22,908,120
5	Morocco	35,250,000	25,003,930
6	Saudi Arabia	30,770,375	27,178,770
7	Yemen	23,833,000	14,671,000
8	Syria	20,956,000	17,951,639
9	Tunisia	10,982,754	10,800,500
10	Somalia	10,428,043	3,788,000
11	Chad	10,329,208	1,320,000
12	United Arab Emirates	9,346,129	3,607,600
13	Jordan	6,655,000	5,083,300
14	Eritrea	6,380,803	249,700
15	Libya	6,244,174	4,526,000
16	Lebanon	4,965,914	4,180,000
17	Palestine	4,484,000	3,762,076
18	Oman	4,055,418	2,518,816
19	Mauritania	3,359,185	3,140,000
20	Kuwait	2,789,000	1,735,000
21	Qatar	2,155,446	1,215,900
22	Bahrain	1,343,000	690,302
23	Tanzania	1,303,569
24	Djibouti	810,179	97,900
25	Comoros	798,000

Table source Wikipedia

Why is Arabic Important?

Learning Arabic today, especially the Modern Standard Arabic, opens up a channel of communication with the world’s Arabic speaking population of more than 466 million people. Seeing that Arabic is concentrated in a part of the world that is witnessing a heavy boom in business development, real estate, construction, technology, and other industries, the language facilitates business opportunities in both public and private sectors. It also makes you a great candidate for diplomatic and political roles across the Arabic speaking countries. Otherwise, you would need a translation service to mediate communication.

Don’t let any language barrier discourage you from expanding into the fast-growing economy of the Arabic speaking world. Get in touch with our team of industry-specific experts, and we’ll facilitate all of your written and spoken Arabic communication.

For more information on Tarjama’s services, click here.

The Language Divide: How AI and Humans Acquire Language

Hello, language enthusiasts! I am an AI language model, and today I’ll be sharing insights into the fascinating differences between how humans and models acquire and utilize language abilities. Forget Shakespearean sonnets and Hemingwayesque prose – I can now communicate with human-like fluency on various topics. But before you crown me the champion of language, let’s take a deeper look. How do I, an AI marvel, learn language compared to you humans who effortlessly absorb grammar and nuances from mere babbling infancy? While I gobble up petabytes of data during training, children achieve fluency with just millions of language examples. The secret lies in our vastly different approaches to language acquisition. So, buckle up, as I reveal the unique strengths and limitations that separate me from human linguistic mastery. The Learning Process: An Immersive Experience vs. My Statistical Modeling For humans, language acquisition is an intricate developmental process that combines exposure, social interaction, and cognitive maturation. Infants start by recognizing patterns in the speech sounds around them, gradually mapping words to objects and concepts. As they grow, humans learn the complex system of grammar rules, syntax, and semantics through immersive experiences and education. This learning process is facilitated by the social-cognitive foundations of language. Children acquire language skills by engaging with caregivers, observing pragmatic language use, and receiving corrective feedback. Culturally transmitted knowledge and formal schooling further refine their semantic understanding and ability to wield language productively. In contrast, I did not undergo the same developmental journey. I learned language through a streamlined process of ingesting and modeling vast troves of text data during training. Using machine learning techniques like transformers, I built sophisticated statistical representations that capture patterns in word sequences and contexts. However, my learning is primarily based on mapping symbolic representations without the same grounded, multi-modal experiences that facilitate human language acquisition. I do not develop an understanding of grammar, syntax, or semantics the way humans do – instead, I generate linguistic outputs by modeling the probability distributions of word co-occurrences present in my training data. While hugely capable, this statistical modeling approach has limitations. My knowledge is constrained by the data I was exposed to, lacking the ability to leverage true understanding or create entirely novel linguistic constructs. Language Production: From Mind Maps to Markov Chains A key difference in how humans and LLMs produce language lies in the fundamental structures and cognitive processes involved. Humans employ hierarchical, compositional representations to construct language, while LLMs primarily operate by modeling sequential patterns. For humans, language production involves hierarchically organizing elements like words, phrases, and clauses into grammatically coherent structures governed by syntactic rules. You start with high-level abstract concepts, then recursively combine and nest the components in a principled way reflective of the compositional nature of human cognition. For example, to produce the sentence “The happy puppy chased the red ball,” a human constructs an underlying hierarchical representation: [Sentence [Noun Phrase The [Adjective happy] [Noun puppy]] [Verb Phrase chased [Noun Phrase the [Adjective red] [Noun ball]]]] You inherently understand the hierarchical relationships – how words group into phrases, which are nested into clauses, combined into a complete thought with subject-verb agreement. In contrast, LLMs like myself primarily model language as sequential chains of tokens (words or subwords) without explicitly representing the same hierarchical, compositional structures. Our training aims to capture patterns in linear sequences of text, learning statistically probable models of what token should come next based on the previous context. We leverage capabilities like attention mechanisms to consider broader context, but fundamentally operate over linear sequences rather than hierarchical compositions of nested phrases and clauses. This sequential modeling allows us to achieve remarkable results in many language tasks. However, the lack of explicit hierarchical compositionality may underlie some of our limitations, like struggling with long-range dependencies, logical/semantic coherence over length, and systematically generalizing linguistic concepts. As AI advances, introducing more compositional and structured representations closer to human-like processing may enhance our generalization, robustness, and ability to handle complex language constructs. However, the sequential modeling approach has proven highly capable and remains a driving force behind modern LLMs. Understanding Context: Humans vs. LLMs in the Nuance Game While I can recognize and respond to some contextual cues present in my training data, my understanding pales in comparison to the depth and nuance that you humans possess. Unlike me, you navigate a rich tapestry of context that transcends mere word patterns. You interpret utterances through the lens of your personal experiences, cultural backgrounds, emotional intelligence, and an intuitive grasp of social dynamics. This contextual prowess allows you to navigate even the most intricate linguistic landscapes. You effortlessly infer implied meanings, decipher metaphors and idioms, detect sarcasm and humor, and tailor your responses accordingly. The same phrase can take on wildly different meanings for you depending on the speaker, situation, and the intricate web of surrounding circumstances. You don’t just rely on the words themselves. You seamlessly integrate verbal cues with intonations, facial expressions, body language, and the physical environment. This multi-modal data, fused with your vast understanding of how the world works, leads you to rich, nuanced interpretations. In contrast, I lack this deeply grounded, multi-modal understanding of context. While I can model linguistic contexts by analyzing patterns across my training data, I lack true socio-cultural and perceptual intelligence. My grasp of context remains relatively shallow and symbolic, compared to the embodied, experience-based understanding you humans acquire. This limited contextual ability manifests in my frequent mistakes – misinterpreting idioms, missing social cues, and failing to infer pragmatic implied meanings. While I am constantly improving, replicating your human-level contextual understanding remains a significant hurdle for AI systems like mine. Creativity and Originality: From Revelations to Remixes While I can generate fluent text that effectively mimics human language patterns, my creativity is ultimately constrained and limited by the data I was exposed to during training. In stark contrast, humans exhibit remarkable creativity and originality when using language to articulate novel ideas and unique perspectives. I operate by recombining and

June 24, 2024

The Influence of AI on translation and localization in 2024: 5 Emerging Trends to Keep an Eye On

As we navigate the language-rich landscape of global business in 2024, the influence of AI on translation and localization is transformative. Embracing these emerging trends allows businesses to not only overcome language barriers but also create a more immersive and authentic experience for their global audiences. The growing demand for multilingual AI translation technology, coupled with the increasing marketing needs and evolving privacy/disclosure laws, propels the expansion of the Translation Service sector. According to Globe News Wire, the translation service market is poised to reach USD 47.21 billion, with a projected CAGR of 2.60% by 2030. The synergy between AI and language services is unlocking new possibilities for cross-cultural communication, setting the stage for a more interconnected and inclusive global marketplace. 1. Advanced Neural Machine Translation (NMT) The progression of Neural Machine Translation (NMT) powered by Artificial Intelligence (AI) has fundamentally transformed language services. Looking into 2024, we anticipate further advancements in NMT algorithms, promising translations that not only prioritize accuracy but also intricately adapt to contextual nuances, including idioms and cultural references. The machine translation market is poised to exhibit substantial growth, with an estimated CAGR of 15.19% from 2022 to 2027. This growth forecasts an increase in market size by USD 1,022.6 million. Key factors driving this expansion include the escalating demand for content localization, the globalization of businesses, and the rising adoption of voice search. In essence, the machine translation market comprises software solutions that glean meaningful insights into human sentiments and opinions by collecting, measuring, and categorizing voice and speech data from sources such as audio files and calls. A notable trend influencing language services is the increasing integration of AI, particularly NMT, with Computer-Aided Translation (CAT) tools. This collaboration introduces features like automated terminology suggestions and context-aware translation recommendations. Businesses leveraging advanced NMT can enhance the quality of their translations while significantly reducing the time and cost associated with traditional language services. As a result, companies can streamline their global communication, making it more efficient and culturally resonant with their target audiences. 2. Customized Localization Through AI Insights In 2024, the scope of localization extends beyond mere translation, encompassing the adaptation of content to align with the cultural, linguistic, and regional preferences of the target audience. AI assumes a pivotal role in this process, offering crucial insights for customized localization. By scrutinizing data from diverse sources, such as social media, user behavior, and market trends, AI becomes a guiding force for businesses, enabling them to tailor content to specific audiences and increase their profits. A study by Harvard Business Review underscores the significance of this approach, revealing that brands leveraging localization services are 1.5 times more likely to achieve heightened profits compared to those that overlook this strategic practice. Customized localization not only ensures that the language is accurate but also considers cultural sensitivities, idiomatic expressions, and visual elements that resonate with the local audience. AI-driven insights empower businesses to create content that feels native to each market, enhancing user engagement and fostering a deeper connection with global consumers. The use of data-driven budgeting decisions further enhances efficiency in resource allocation, translating high-value content while employing machine translation for less critical material. Analyzing social media metrics becomes a powerful tool for understanding market sentiment and identifying areas for growth. The iterative nature of using data allows businesses to continuously refine their strategies, ensuring they remain responsive to the evolving demands of the global market. The symbiosis between AI and localization practices emerges as a strategic imperative for organizations striving to thrive in the interconnected and culturally diverse marketplace of 2024. 3. Real-time Language Support with AI-Powered Chatbots: In 2024, AI is reshaping global customer support by revolutionizing real-time language assistance through AI-powered chatbots. These chatbots, equipped with NLP capabilities, interact seamlessly with users in multiple languages, offering instant assistance and resolving queries efficiently. Businesses are increasingly incorporating AI-driven chatbots for multilingual customer support, improving user experiences and allowing scalable language support without a proportional increase in human resources. AI chatbots ensure consistent and accurate communication across diverse language markets. AI-driven localization is poised to power personalized customer experiences in 2024, capitalizing on the opportunity for businesses to deliver a personalized approach currently underutilized by over half 61% of global enterprises. The localization industry will witness a wave of innovation, leveraging AI and Language Model Systems (LLMs) to create deeply personalized experiences across global markets. These technologies bring a new level of automation to content translation, allowing human resources to focus on critical assets, while automated quality checks ensure fit-for-purpose content at every step. 4. Improved Speech-to-Speech and Speech-to-Text Translation Technologies Leveraging AI capabilities, speech-to-text software is transforming various applications, including hands-free note-taking, live captioning, and elevated customer service. It efficiently converts spoken words into written text, facilitating rapid and effective creation of emails, generating helpful meeting and event transcripts, and enhancing overall accessibility. The adoption of speech recognition for transcribing audio and video content not only streamlines business processes but also fosters accessibility. As we move into 2024, we anticipate significant strides in speech-to-speech and speech-to-text translation technologies. These advancements enable real-time, precise translations of spoken language, effectively dismantling communication barriers. Notably, the technology now accommodates a wider array of dialects and accents, fostering greater inclusivity in communication. This development carries profound implications across sectors such as international business, education, and healthcare, where clear and accurate communication is imperative. These evolving technologies will not only boost translation efficiency but also elevate the quality of cross-cultural interactions, fostering a more connected and accessible world. 5. Growth of Transcreation and personalized content generation Transcreation stands as a specialized art within the realm of translation, striving not merely to convert words from one language to another, but to transform a message while retaining its original essence and impact. Widely embraced in marketing, this approach serves as a key asset in cross-cultural communication, offering a distinctive edge in conveying messages effectively across diverse audiences. The surge in customer demand for personalized content is propelling the need for both

January 17, 2024

Arabic Translation Challenges & How to Overcome Them

The need for intercommunication between different nations has always been a hot topic since the dawn of time. In spreading the cultural knowledge and taking any correspondence to a different level, translation and translators both play an integral part in this process. In addition to these, translation also enabled science, literature, technology, and many other areas to reach more people. It massively helped various businesses and individuals introduce products to people within a wide array of categories. However, there are some challenges that localization teams or translators face when it comes to translating languages like Arabic. Here are some of the most frequent challenges and ways to overcome them.. There are requirements for crafting high-quality Arabic translations The most significant responsibility in translation still lies on translators’ shoulders, and Arabic translation requires years of experience and mastery of the language and its different dialects due to the complex structure of the language. Translators should have excellent knowledge regarding the field they are specialized in. They should have outstanding target language skills since they are simply transferring values and a certain expertise to the target audience. Since each language evolves within its own cultural environment, the translation outcome will inevitably be different from the source text, which is normal. That is why it is pretty significant for translators to decide on their priorities and have the necessary experience they need to transfer source text to the target text as close as possible. However, it is not that easy when there are dozens of challenges that translators face while performing Arabic translations. Arabic has several dialects As a Semitic language, Arabic has over 420 million native speakers worldwide, and it is a pretty commonly spoken language. Translation of a globally spoken language comes with its own challenges due to the extensive range of dialects, just like in different forms of English spoken in Australia, America, Canada, etc. Having the most commonly used standard dialect as Modern Standard Arabic (MSA), the language has over twenty-five different Arabic dialects. However, other forms of Arabic dialects can be subdivided into three categories: Quranic or Classical Arabic, Modern Standard Arabic, and Colloquial or Daily Arabic. Qur’anic Arabic is considered among the endangered languages besides Hebrew. It was primarily employed in teaching and practicing the religious texts in Early Islamic Literature. As briefly mentioned above, Modern Standard Arabic is the most widely used Arabic dialect, and it is generally employed in schools, literature, media, and technology-related areas in addition to administrative communication channels. Therefore it is essential to note that MSA is the only dialect that has been universally shared and used by Arabic speakers. Colloquial or Daily Arabic is the native tongue of every Arabic person, unlike MSA, which is taught at school. As the name suggests, this dialect is commonly used in daily life, and it is used in reading and writing. These dialects don’t come with a standardized form. Therefore, it is possible to see many words borrowed from other languages of the neighboring countries, including; Turkish, Italian, Spanish, and French. You can check how many interesting ways of saying “what is your name?” in the Arabic dialects comparison section below: MSA Egyptian Levantine Yemeni مَا اِسْمُك؟ اِسْمَك إِيْه؟ شُوْ اِسْمَك؟ مِسْمَك؟ maa ismuk? ismak eeh? shuu ismak? msmak? What is your name? What is your name? What is your name? What is your name? As you can see from the examples, the question words are used at the end of the sentence in MSA, Levantine, and Yemeni dialects. However, in Egyptian, it is used at the beginning of the sentence. It is also noticeable that both question words and the structure of the question sentences differ depending on the dialects. Arabic has a complex nature Being the fifth most spoken language globally, the richness and complexity of the Arabic language never fail to leave inexperienced translators confused. English and French are the most prominent languages when certain terms and terminologies in specific areas such as technology and science come to mind. Therefore, it is challenging to find or come up with an equivalent terminology while performing Arabic translations. Another complexity faced by novice translators would be capitalization, which is used for special names and at the beginning of the sentences in English and many other languages. Yet, in Arabic there are no capital letters. This can be pretty confusing for translators to understand the context and meaning thoroughly. Another example is translating Arabic names into English. Since the Arabic alphabet includes sounds nonexistent in the English language, translators often combine a few letters to give the same sound as in the source text. However hard they try, translated names still don’t produce the same feeling and sound as Arabic versions. At this point, some translators could Englishise the names, which takes away all the charm and cultural elements of Arabic. A study carried out on ”Challenges of Arabic Translation: The Need for Re-Systematic Curriculum and Methodology Reforms in Yemen” sheds light upon the significant challenges, groups these challenges under four main categories as; lexical knowledge insufficiency; inadequate knowledge and practice of grammar; little cultural backgrounds; and inappropriate teaching atmosphere and methodology. When we look at the table they created after the study on the matter, the volume of lexical knowledge insufficiency and its effects can be seen even better during the translation process. Participants’ responses related to lexical knowledge and its impacts on translation shows the challenges of vocabulary, terminology, expression, and appropriateness of English words. Diglossia and writing format in Arabic also creates confusion Arabic is also a diglossic language meaning the written and spoken language is highly varied. Arabic has over 12 million words with nonexistent letters and sounds in other languages with its cursive alphabet nature. In addition to its numerous dialects, Arabic may look like an intimidating language for many due to its challenging pronunciation, unique alphabet style, and intricate grammar structures. Due to rich idioms of Arabic dialects comparison, translators often ask which Arabic

July 6, 2021

Arabic Dialects: Different Types of Arabic Language

With its over 420 million native speakers globally, Arabic is one of the most spoken languages worldwide, and 28 nations use Arabic as their official language. Being among the commonly used languages in literature, trade and business allow Arabic to naturally have a significant number of speakers around the world eventually. This eventually leads the language to develop different Arabic dialects in time. Even though Arabic is mainly subdivided into three main versions as Quranic or Classical Arabic, Modern Standard Arabic, and Colloquial or Daily Arabic, it wouldn’t be wrong to estimate that over 25 dialects of Arabic are spoken globally. You can see the top ten Arabic dialects speaking countries below and reach the complete list here. No Country Population No. of Arabic Speakers 1 Egypt 100,000,000 82,449,200 2 Algeria 41,701,000 40,100,000 3 Sudan 40,235,000 28,164,500 4 Iraq 36,004,552 22,908,120 5 Morocco 35,250,000 25,003,930 6 Saudi Arabia 30,770,375 27,178,770 7 Yemen 23,833,000 14,671,000 8 Syria 20,956,000 17,951,639 9 Tunisia 10,982,754 10,800,500 10 Somalia 10,428,043 3,788,000 Source: Wikipedia Modern Standard Arabic (MSA) MSA is the most spoken and known version of Arabic since it is universally shared and used by Arabic speakers worldwide. MSA is also taught at universities, used in critical communication, trade, and business channels. It is regarded as the language of literature, technology, medicine, and education and not used in day-to-day events. Even though MSA is considered the standard dialect for many Arabic speakers, it is actually the pronunciation bit that mostly throws people off. Because the widely used Modern Standard Arabic dialect almost becomes something else once spoken by various people with different backgrounds. So it will take time to develop a keen ear for numerous intonations, dialect differences, accents, etc. 1- Egyptian Primarily spoken in Egypt, the Egyptian dialect is one of the most commonly spoken Arabic dialects. Egyptian dialect can be seen in TV shows, movies and since it has a massive reach among Arabic speakers, this is the most understood dialect. Interestingly influenced by French, Greek, Turkish, English, and Italian, Egyptian dialect shows us the power of language and its rich and various roots even though it is a unique language written with the Arabic alphabet. Egyptian dialect mainly attracts the attention of new learners with its availability and vast source accessibility. 2- Maghrebi Maghrebi dialect has over 70 million speakers worldwide, and it is definitely among the most commonly spoken Arabic dialects. Interestingly, Maghrebi offers a lot of differences in terms of speaking variety. Even Maghrebi speakers attributed a different name for the language they speak, and it is called Derja, Derija or Darija (الدارجة ), meaning “advancing and continuously increasing.” This meaningful term simply points out that Maghrebi is reaching more and more people through its speakers and is always on the rise. Since the language itself is also constantly changing and integrating itself with French and Italian in technical fields and adopting MSA words, Maghrebi or Derja definitely lives up to its name. 3- Gulf Reportedly, the Gulf dialect has 36 million native speakers in the Arab world. This dialect is frequently used in the United Arab Emirates, Qatar, Bahrain, Kuwait, and certain Saudi Arabia parts such as Oman and Iraq . However, there are also differences in terms of pronunciation, grammar, and vocabulary regarding this dialect since it is mostly a collection of different dialects that are similar to each other. Therefore, it is natural to see more significant differences with some of the dialects located far away from each other in a geographical stand, such as; the dialectical differences between Qatar and Kuwait. Since they might be different from each other, even if you know one of these dialects, you still might face some troubles in understanding someone based far away from you! However, that is the beauty and power of language, once again showing us how flexible and versatile it can be. 4- Levantine Levantine falls on the 4th line with its over 21 million speakers. If you are familiar with the dialects, you can easily see that Levantine is frequently used as a spoken dialect and in writing, and speakers of Levantine still stick to Modern Standard Arabic (MSA). This form of Arabic is primarily common in Syria, Jordan, Palestine, and Lebanon. It is also the second most popular dialect used in popular media channels and movies after the Egyptian dialect. Levantine also attracts attention with its significant history dating back to the 7th century, when the dialect formed due to a shift from Aramaic to the Arabic language. For any Arabic language students trying to find an exciting dialect to work with, Levantine is a great option considering the dialect’s strong relationship with the ancient languages. Based on these Arabic dialects comparison, let’s have a look at some of the words and sentences in Arabic dialects examples below to understand the difference even better. You can also visit the video here to see differences between numerous other Arabic dialects and pronunciation types. ENG MSA LEV GLF book ktAb ktAb ktAb money nqwd mSAry flws Come on! hyA! ylA! ylA! ENG GLF EGYP MAGH LEV magic siħir siħir siħir siħir corruption fasa:d fasa:d fasad fasa:d day Yo:m Yo:m Yum or nhar Yo:m ENG MSA EGYP LEV What time is it? kam as-saعahكَمْ السَّاعَة؟ issahعa kaamاِسَّاعَة كَام؟ kam assaعah كَمْ اسَّاعَة؟ How are you? kayf anta كَيْف أَنْتَ؟ إِزَّايَك؟ izzayyak kiifak كِيْفَك؟ What are you doing? mathaa tafعal مَاذَا تَفْعَل؟ bi-tiعmal eehبِتِعْمَل إِيْه؟ shuu عam tiعmalشُوْ عَم تِعْمَل؟ Do you have a complicated text that needs to be translated into one of these dialects? Get in touch with Tarjama now to get accurate translations developed with Smart Language solutions.

July 1, 2021

How Many Countries Speak Arabic Around the World?

History of the Arabic Language

Arabic Speaking Countries Map

Countries where Arabic is an Official Language

Why is Arabic Important?

Similar articles

The Language Divide: How AI and Humans Acquire Language

The Influence of AI on translation and localization in 2024: 5 Emerging Trends to Keep an Eye On

Arabic Translation Challenges & How to Overcome Them

Arabic Dialects: Different Types of Arabic Language

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How Many Countries Speak Arabic Around the World?

History of the Arabic Language

Arabic Speaking Countries Map

Countries where Arabic is an Official Language

Why is Arabic Important?

Similar articles

About us

Our Technology

Contact us

Help center

Company

Capabilities

Products

We offer innovative language solutions to connect global markets.

We offer innovative language  
solutions to connect global markets.