The world is beautifully diverse. While we are divided by geographic locations, frontiers, languages, ideologies, and more, we are united by emotions and the way we understand them sometimes through unspoken words.Unfortunately, computers and machines don’t understand emotions and abstract feelings – yet. Though Artificial Intelligence (AI) is dynamically spreading its wings across industries and market segments, we are yet far from playing charades with it unless we are familiar with English.And because the world is rich in diversity, it becomes essential to make the internet accessible and inclusive for all people regardless of whether they speak Mandarin Chinese, Japanese, Espanol, Hindi, Russian, or more.This is exactly why multilingual AI text data becomes crucial in training AI, specifically Natural Language Processing (NLP) modules. In order for machines to deliver human-like experience across languages and geographies, turning AI algorithms into polyglots is the first step.In this article, let’s explore why it is crucial and some use cases and benefits of doing so.4 Reasons Why Machine Learning Models Should Be Trained in Multilingual AI Datasets1. Improve User Experience & AccessibilityNative language user experience is a distinct approach that can change the game for businesses. A report on consumerism reveals that over 55% of the global users prefer to buy products from websites that provide content in their native languages. Besides, websites based on English alone are overlooked by over 87% of the consumers.While the statistics may not be directly influential, they offer us a peek into the subliminal traits of users. That’s why training models using multilingual AI text data is beneficial for businesses to present content and messaging across their apps, websites, emails, customer services and more in different languages.2. Gain A Global Competitive EdgeBeing multilingual can help individuals seamlessly navigate complexities of the world and find a sense of belonging wherever they go. AI is no exception. For businesses that intend to expand their services and offerings across the globe, utilizing multilingual AI datasets to train their models helps exponentially.In the age of localization and hyper-personalization, this strategic move can let businessesexplore new business opportunitiestap into existing markets by diversifying vertically and horizontallydeliver exceptional customer services and pave the way for faster and more dependable conflict resolutions and more3. Mitigate Bias and Consider Cultural SensitivityCancel culture is the modus operandi of netizens today and the internet is swift to take offense at the drop of a hat. When training AI models, it is inevitable that bias is introduced. Such bias can prove extremely harmful to businesses when fetching one-sided results that are either favorable or outright offensive.However, multilingual AI datasets can help mitigate this bias as they introduce cultural diversity through language-specific intricacies, pronunciations, nuances, context, and more to formulate appropriate responses. This can range from humorous comebacks to sarcastic jibes that only positively elevate user experience and ultimately brand loyalty.4. Multi-language Insights RetrievalDespite the world being extremely connected, portions of data and information still remain in silos as indecipherable. Language is a barrier in enabling comprehension of such data that could be of use to businesses and users.When machine learning models are trained in multiple languages, information that was once non-comprehensible starts making sense. Such insights could turn the tables for businesses in making informed decisions pertaining to specific geographies.An Overview Of Benefits Of Multilingual AI Datasets Across IndustriesRetail & eCommerce
Localization of content in the form of product descriptions, reviews, customer support, and moreImproved customer satisfactionIncreased sales, conversions, and repeat purchasesPrecision sentiment analysis and optimized ORM strategiesBanking & Finance
Airtight compliance of regulations, mandates, and compliances that are specific to particular geographiesSeamless analysis of claims, insurance policy details, documents, and more in regional languagesEducation
Availability of vernacular educational contentImproved accessibility to learners, resulting in retention and sustained interests in completing online learning modulesDemocratization of education, where people can learn Python (for instance) in a language of their choice like SwahiliTravel & Hospitality
Real-time translation services of phrases, texts, and voicesAutomatic translation of local details such as booking vouchers, messages, travel recommendations, menu cards, do’s and don’ts and moreIncreased scope for lead generation through vernacularization of content