In India, 75 percent of the population interact with the Internet using their native language, and sometimes as it happens the users are unable to find their desired location on Maps in their native.
Google Maps is introducing automatic transliteration which will help users in delivering a more intuitive language experience and will enable search queries in their own languages and find information. The main issue faced was that the names of most Indian places of interest in Google Maps are not generally available in native Indian scripts. These names are in English and combined with acronyms based on the Latin script, as well as Indian language words and names. To address such a system Transliteration is required that maps characters from one script to another while accounting for the phonetic properties of the words as well.
Cibu Johny, Software Engineer, Google Maps explained how the feature works. He says, “Common English words are frequently used in names of places in India, even when written in the native script. How the name is written in these scripts is largely driven by its pronunciation. For example, एनआईटी from the acronym NIT is pronounced ‘en-aye-tee’, not as the English word NIT. Therefore by understanding that NIT is a common acronym from the region, Maps can derive the correct transliteration. In the past when Maps could not understand the context of एनआईटी, it would instead show a related entity that might be farther away from the user. With this development, we can find the desired result from the local language query. Additionally, users can see the Places Of Interest names in their local language, even when they do not originally have that information.”
Google has built an ensemble of learned models to transliterate names of Latin script Places Of Interests into 10 languages prominent in India: Hindi, Bangla, Marathi, Telugu, Tamil, Gujarati, Kannada, Malayalam, Punjabi, and Odia. This will benefit hundreds of users in India who do not speak English and help them in finding doctors, hospitals, grocery stores, banks, bus stops, train stations, and other essential services in their own language.
For a deep dive on how Google has implemented this feature, have a look at the blog post by Google linked here.