Language learning app powered by artificial intelligence He speaks On a tear.
Since launching in its inaugural market of South Korea in 2019, Speak has grown to more than 10 million users, CEO and co-founder Connor Zwick told TechCrunch. Its user base has doubled every year over the past five years, and Speak now has customers in more than 40 countries.
Eager to see the talk expansion Completeinvestors are now pledging additional funds to the startup.
The company this week closed a $20 million Series B extension led by Buckley Ventures, with participation from OpenAI Startup Fund, Khosla Ventures, Y Combinator co-founder Paul Graham, and LinkedIn CEO Jeff Weiner. The capital infusion brings Speak’s total valuation to $84 million and doubles the startup’s valuation to half a billion dollars.
Speak, was launched in 2014 by Zwick and Andrew Hsu, who met while at Thiel Fellowship, is designed to teach language by having users learn speaking patterns and practice repetition in prepared lessons rather than memorizing vocabulary and grammar. In this way, it’s no different from Duolingo, especially Duolingo Latest features of generative AI. But true to the verb of the same name, Speak emphasizes pronunciation above all else.
“Our core philosophy is to get users to speak as loudly as possible,” Zwick said. “Achieving fluency helps people make connections, connect cultures, and create economic opportunities. It remains the most important part of language learning for people, but it has historically been the least supported by technology.”
Speak started out in English, and has since launched Spanish lessons, powered by a speech recognition model trained on internal data. Next is French, but Zwick didn’t say exactly when she would launch classes for that.
Speak makes money by charging $20 a month, or $99 a year, for access to all of the app’s features, including review materials and one-time courses.
With a workforce of 75 people across offices in San Francisco, Seoul, Tokyo and Ljubljana (the capital of Slovenia), Speak’s near-to-long-term roadmap is developing new models that provide better real-time feedback on intonation and pronunciation, Zwick said.