Your chatbot or assistant's users are used to speaking in more than one language, and you need to be able to talk to them in their own language, or else they'll lose interest.
Texts in the web can be found in different languages, and you may be only interested in a specific one. Most language identifiers only work with very large texts, not at sentence level, so they aren't useful either for user queries, like tweets or interactions with AIs.
Bitext Language Identification is the most practical and accurate solution in the market because it's based on script and grammar knowledge. Some of its unique features include:
High accuracy even with small texts. Most approaches in language identification only work with very large texts, because of their probabilistic methods. They depend entirely on the amount of data to analyze. Our linguistic knowledge, on the contrary, allows us to achieve high performance even for short inputs.
Recognizes the language for each sentence. Other approaches can detect what percentage of a given document is written in which languages, but fail to tell exactly what parts of the text belong to each language. However, this is a fundamental information you need to have, in order to properly react to each sentence.
Able to identify over 50 languages or dialects.
Don't deploy 2 different bots or VAs, instead centralize all interactions in a bilingual one. Enable it to respond in any language at any point in the conversation. Wouldn't it be wonderful to have bots as adaptive and versatile as human beings?
Digital humanities scholars find it hard to extract texts written in less-known languages, which are their focus of study. These languages usually come from multilingual web pages containing other massive-spoken languages, such as English, so they have to tell them apart. With Bitext Language Idenfitication software, this becomes a much easier task.
Building corpora? Looking for texts in the Web? You may have encountered texts in a mixture of different languages, only one of which you are interested on. Simply use language identification as a pre-filtering step to improve the quality of input data of your system and therefore improve its performance.
The software is currently capable of recognizing over 50 languages: Afrikaans, Arabic, Azerbaijani, Belarusian, Bulgarian, Catalan, Czech, Danish, German, Greek, English, Esperanto, Spanish, Estonian, Basque, Farsi, Finnish, French, Irish Gaelic, Galician, Gujarati, Hebrew, Hindi, Hungarian, Armenian, Indonesian, Icelandic, Italian, Japanese, Georgian, Kazakh, Kannada, Korean, Kyrgyz, Macedonian, Malayalam, Mongolian, Malay, Norwegian Bokmål, Norwegian Nynorsk, Nepali, Dutch, Punjabi, Portuguese, Russian, Slovak, Serbian, Swedish, Swahili, Telugu, Tagalog, Turkish, Ukrainian, Urdu, Uzbek, Vietnamese, Chinese and Zulu.
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