These days, Xu Li doesn’t worry whenever her elderly father takes off on one of his frequent solo trips to Europe. Although the native of provincial capital Hefei speaks little English and has Chinese so heavily infused by his city’s local patois that other Chinese cannot always understand him, Xu trusts that, in case of an emergency, he can communicate using the dialect transcription and translation app on his phone. After all, she helped develop the program.
Xu is a researcher at iFlytek, a Chinese tech firm known for its AI-powered iFlytek Voice Input keyboard app. The app’s voice-to-text function lets users transcribe vocal recordings and dictate written messages. But to win over consumers and succeed in the Chinese market, it needs to do more than just be able to recognize and translate spoken Standard Mandarin, the country’s only official national language — it has to be able to understand and process dialect, too.
That’s where Xu comes in. Despite decades of concerted government effort, tens of millions of Chinese, including Xu’s father, still speak little-to-no Standard Mandarin, instead communicating in one or more of the country’s thousands of distinct regional and local vernaculars. It’s Xu’s job to increase the accuracy of iFlytek’s input method — and the software’s potential scope — by using deep learning techniques to teach the program these dialects.