Microsoft has announced the addition of 13 new African languages to its Azure Cognitive Services Translator, enabling text and documents to be translated to and from these languages across the entire Microsoft ecosystem of products and services. The latest languages added to the platform include Sesotho (Southern Sotho), Sesotho sa Leboa (Northern Sotho), Setswana (Tswana), and Xhosa, which are the latest of South Africa’s official languages to be supported, following last year’s release of Zulu. The other languages are chiShona, Hausa, Igbo, Kinyarwanda, Lingala, Luganda, Nyanja, Rundi, and Yoruba. This brings the total number of supported languages to 124, adding language support for millions of people in Africa and worldwide.
Microsoft aims to break down language barriers and empower local communities by developing meaningful cognitive products and services that improve accessibility. Integrations across Microsoft’s ecosystem include Microsoft 365 for translating text and documents, the Microsoft Edge browser and Bing search engine for translating whole webpages, SwiftKey for translating messages, LinkedIn for translating user-submitted content, and the Translator app for having multilingual conversations on the move, among others.
Translator can add African languages’ text translation to apps, websites, workflows, and tools or translate entire documents, or volumes of documents, in a variety of different file formats preserving their original formatting. Users can also use Translator with Cognitive Services such as Speech or Computer Vision to add additional capabilities such as speech-to-text and image translation into their apps. Educators can create a more inclusive classroom for both students and parents with live captioning and cross-language understanding.
Microsoft Research developed machine translation systems more than a decade ago, and has continuously added languages and dialects to the service, while ensuring the translation quality of the supported languages by using the latest neural machine translation (NMT) techniques. The company has migrated all machine translation systems to neural models to improve translation fluency and accuracy. Working with partners in language communities who can help gather data for specific languages and who have access to human-translated texts also helps to overcome the challenge of obtaining enough bilingual data to train and produce a machine translation model.
These ever-improving capabilities make it possible for businesses to expand their global reach, enabling them to communicate with customers and partners across languages and localise content and apps quickly, reliably, and affordably. There are plans to add more of the continent’s most widely spoken languages as part of Microsoft’s mission to build meaningful cognitive products and services that improve accessibility and local engagement. The addition of new African languages means that more people are able to connect, and that language will become a seamless feature of using technology.
