Azure AI empowers organizations to serve users in more than 100 languages

Microsoft announced today that 12 new languages and dialects have been added to Translator. These additions mean that the service can now translate between more than 100 languages and dialects, making information in text and documents accessible to 5.66 billion people worldwide.

“One hundred languages is a good milestone for us to achieve our ambition for everyone to be able to communicate regardless of the language they speak,” said Xuedong Huang, Microsoft technical fellow and Azure AI chief technology officer.

Translator today covers the world’s most spoken languages including English, Chinese, Hindi, Arabic and Spanish. In recent years, advances in AI technology have allowed the company to grow its language library with low-resource and endangered languages, such as Inuktitut, a dialect of Inuktut that is spoken by about 40,000 Inuit in Canada.

The new languages and dialects taking Translator over the 100-language milestone are Bashkir, Dhivehi, Georgian, Kyrgyz, Macedonian, Mongolian (Cyrillic), Mongolian (Traditional), Tatar, Tibetan, Turkmen, Uyghur and Uzbek (Latin), which collectively are natively spoken by 84.6 million people.

Removing language barriers

Thousands of organizations have turned to Translator to communicate with their members, employees and clients around the world. The Volkswagen Group, for example, is using the machine translation technology to serve its customers in more than 60 languages. The workload involves translating more than 1 billion words each year. The company started with standard Translator models and is using the custom feature in Translator to fine tune these models with industry specific terms.

The ability for organizations to fine tune pre-trained AI models to their specific needs was core to Microsoft’s vision when it launched Azure Cognitive Services in 2015, according to Huang.

In addition to language, Azure Cognitive Services include AI models for speech, vision and decision-making tasks. These models enable organizations to leverage capabilities, such as a Computer Vision technology known as Optical Character Recognition (OCR). This service extracts text entered on a form in any

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