Google Now and Reddit joined forces for better speech recognition

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Google Now wants to improve its voice recognition engine in order to understand different accents

Google Now

source: https://googleblog.blogspot.gr/2013/04/google-now-on-your-iphone-and-ipad-with.html

Google’s famous voice assistant, Google Now, has a very interesting aspect. It can detect the different tones of the human speech. For that you can thank the combination of machine learning and the all the date they have gathered. It can analyze murmurs and mumbles even the most garbled phrases. But, there are some elements that Google Now seems to have a slight weakness. And that is different accents.

But, Google is going to improve that by recruiting users of Reddit. According to reports the infamous social network Reddit is calling voice volunteers to work for Google. But they are not alone on this task. They have asked the help of a third-party firm, called Appen. The company has started recruiting Reddit users with specific accents. Their goal is to improve Google’s voice recognition engine.

The terms of use and training are simple. According to The Verge, the selected participants were directed to a mobile onboarding webpage. The webpage featured a “record” icon on that page. When they tapped it phrases appeared in sequence. The people who talked to The Verge about the experience had a mixture of accents. From the U.K. and America to Indian and Chinese-accented English.

Some of the phrases were focused on Google, such as “OK Google,” and “Hey, Google”. In addition the participants had to read brand names, toys, video games, movie titles, and YouTube channel names.

At the end of the recording the data are collected and processed by Appen’s in-house team. Mark Brayan, from Appen, shared some details about the project to The Verge. The team analyze recordings from “around the world” in 130 languages. Then they carefully distilling sentences down into their grammatical fundamentals.

But processing all these data is not an easy job. According to Brayan even small improvements require massive quantities of data and analysis.

“To go from understanding 95 percent of words to 99 percent, the recognizer has to digest infrequently used words, of which there are millions,”

“One of the big challenges is what we call named entity recognition,” Brayan said. “That’s brand names, product names, individual names, and so on. So if you’re launching in Canada, for example, you need not only the French language but also French-accented Canadian English.”


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Author: Martha Papadimitriou

Martha is a journalist, a blog writer, a mother and a bookworm. She studied Journalism and Communication and graduated in 2002. She has a restless spirit and loves to learn new things. Martha also wants to make the world a better place, and when she is not working she enjoys reading and cooking.

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