Make Your AI Solutions Global with Multilingual NLP Tools

In an era of globalization, being multilingual is essential for business. Either for your e-commerce bot to understand international customers, or for your feedback management platform to get insights from every user, English is not enough. 

 

The ongoing increase in interaction and integration between countries and regions worldwide is a clear sign that multilingual issues are here to stay. Chinese, English, Hindi, Spanish and Arabic are the most widely spoken languages around the world. If your current AI system is just supporting one or two of them, it’s crystal clear that you are not covering the entire market. Your customers could be anywhere around the globe and speak any given language. Don’t you think it would be worth to consider how important offering multilingual services is in order to understand your customers’ needs?

 

There is a wide range of enterprises claiming to offer a great variety of Natural Language Processing tools. However, most NLP applications focus on major languages and standardized language varieties. From a technical point of view, this focus may be comprehensible since AI systems are most likely to be used on data of a standard variety which is easier to find. Nevertheless, the linguistic reality is rather more complex in many regions of the world where speakers tend to use non-standard language varieties. That’s why it is crucial for any business to include as many languages and variants as possible in their AI solutions.

 

Bitext is offering full NLP building packages for a proper understanding of more than 75 languages and their variants. This offering includes:

  • Language detection tools to identify what language a text is written in, even in multilingual texts/queries.
  • Spelling suggestions to avoid typos as confusion triggers.
  • Splitting tools like segmenters and tokenizers, preprocessing steps to be followed by a grammatical analysis.
  • POS-Taggers and lemmatizers to guarantee a successful comprehension.
  • Phrase extraction tools to extract all relevant noun, adjective, verb or adverbial phrases.
  • Lexical dictionaries to gather a more detailed compilation of data with their grammatical attributes such as gender, number, tense…

 

As already mentioned, it’s true that most companies just have NLP support for the English language. When these companies receive data in any other language, they are forced to first translate these data into English. No need to say that this solution is error-prone due to nuances, context or particular expressions difficult to render, resulting in unreliable grammatical analyses. Therefore, these analyses must be done in the native language so that the NLP procedure succeeds.

 

The map below shows the up-to-date language coverage available supported by Bitext NLP services, including minority languages such as Sindhi or Irish Gaelic.

Bitext Languages-01

Click here to see the whole list of languages available for those linguistic resources.

 

Apart from all core NLP services, there are also customer experience analytics solutions such as categorization, topic-based sentiment analysis and entity extraction with GDPR, available in the native language of the feedback. Here, the AI system can be customized to meet any business’ specific needs by creating their own categories or tuning sentiment according to any particular requirement. Not long ago, Bitext achieved considerably accurate results (up to 90%) in projects supporting categorization in 21 languages, for instance Swiss German. Click here to see a case study made for the automotive industry.

 

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