“You don’t have to type those things in, but we try and guess using translation, which is another one of these sorts of techniques that has come a long way,” he explains how this new technique helps solve the problem of input in Indian languages. So now it’s just a tap to flip over to those results and see whether those are better for you or not,” he explains the latest feature Google is rolling out in India. “The other strategy is that we can take your English query and depending on the query we either translate it or we transliterate it to your regional language and show results for that. “They work reasonably well but I think we want to make it much better so that it becomes really easy to do this without error.” The work that has already gone in has started showing some results. And that is why he says Google has a “big investment in improving speech recognition for Indian languages” and “getting the right data for training data, the right algorithms in place”. While it is still quite tough to type and search in regional Indian languages, Nayak accepts “having speech recognition as a mode of operation is incredibly valuable”. And by having the right training data, you can learn the right sensibilities.” “As long as you have the right training data in terms of documents in that language and so forth. “Fundamentally, the techniques we use tend to be statistical techniques that look at sort of large scale statistics of language and language usage… it’s not that we learn English grammar and then Hindi grammar and so forth,” he says, adding how since the underlying techniques are statistical in nature, they can generalise very easily to many different languages. But the statistical approach made this a bit easier. Then there was the problem of taking these learnings to other languages, what Google calls localisation. “Getting that right is essential to being successful with your users.” “If you don’t do a good job, people are not going to use your product as language is so central to us,” he adds.

Because language is this sort of complex thing… it is very subtle, nuanced and whatnot,” he tells, adding how the more recent innovations have been around machine learning and deep learning, “sort of quantum leaps forward in understanding sentences, natural language and conversations”.Īlso read: Google Search to show results in relevant local language even if you type in English characters “You get all these really interesting phenomena with language. While it has progressed, Nayak accepts that they “didn’t quite get it right” as still you will see some results for the sole of a shoe when someone is actually searching for the fish. Then came the phase of language understanding where the engine started to understand the difference between the ‘sole’ of a shoe and ‘sole’ fish. “Subsequently, the next big innovation in language was around synonyms… the idea that words mean different things in different contexts,” he continues. “So one of the first things that was sort of (we did) language oriented was spelling correction.” While that might seem very simple now, Nayak, who is part of Google’s core Search leadership team, clarifies that “having a clever way to spell actually requires you to understand language”. And, and you can see that in the evolution of search from the early days,” he explains on a video call. “Language is at the very heart of what we do. The Google Fellow and VP – Search has been on the job for 16 years. Pandu Nayak knows all the effort that has gone in. As Google now starts understanding even Indian languages written in Roman script and figuring out which language to surface for which query, it would be the culmination of work that started a long time back.

Pandu nayak google