A startup called Palabra AI, which develops an AI-powered speech translation engine, is tackling one of the more difficult aspects of teaching Large Language Models (LLMs) to understand multiple languages.
Today, LLMs make it easier to convert text from one language to another, but speech translation is not as simple, according to Reddit co-founder Alexis Ohanian.
“AI can generate content and translate text. But [Speech] Translation is a unique problem because it requires real-time language switching, and the voice also needs to sound human,” Ohanian said.
Ohanian and his venture firm Seven Seven Six (776) believe that Palabra AI could be an answer to that problem. That’s why the firm is leading an $8.4 million pre-seed round into the startup. The round also saw participation from Creator Ventures along with individual investors, including Instacart co-founder Max Mullen; former a16z partner Anne Lee Skates; former DeepMind Head of Product at Mehdi Ghissassi; and Namat Bahram.
Seven Seven Six’s Ohanian also noted that Palabra’s combination of product execution and team expertise pushed the firm to invest.
“With Palabra, the translation layer works very smoothly. The company has a strong AI research team that does high-quality work around speech. Plus, the startup has made great choices in product design and quality of output,” he added.
Palabra was founded by Artem Kukharenko and Alexander Kabakov in 2023. Kukharenko, a former machine learning engineer at Samsung, said that he has lived in various countries as a digital nomad and faced problems with languages. That’s why he wanted to combine his machine learning experience to solve for real-time translation.
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CEO Artem Kukharenko Image Credits: Palabra
“Many other companies have tried to solve the translation problem. But when they combined different pieces of tech, including speech-to-text and text-to-speech APIs while translating, the latency number increased, and the translation didn’t feel real-time. With Palabra, we have been able to bring down the latency to 800ms, making our translation seamless and real-time,” he told TechCrunch over a call.
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