DeepL, renowned for text translation, now targets voice translation

DeepL, a translation company best known for its text-based tools, has launched a voice-to-voice translation suite today that addresses scenarios such as meetings, mobile and web conversations, and group discussions for frontline workers through custom applications. The company also introduced an API that enables external developers and businesses to build upon DeepL's technology for tailored use cases, such as call centers.

"After spending so many years focused on text translation, voice was a natural next step for us," DeepL CEO Jarek Kutylowski told TechCrunch in an interview. "We have made significant progress in text and document translation. But we felt there wasn't a great product available for real-time voice translation."

Kutylowski explained that the main challenge in developing a real-time translation product involves finding the right balance between reducing latency—the delay between when someone speaks and when the translated audio is heard—and maintaining high accuracy.

DeepL is releasing add-ons for platforms like Zoom and Microsoft Teams, where listeners can either hear real-time translations while others speak in their native languages or follow real-time translated text on screen. This program is currently available through early access, and the company is inviting organizations to join a waitlist. DeepL also offers a product for mobile and web-based conversations, whether conducted in person or remotely.

DeepL also enables users to participate in group conversations in settings such as training sessions or workshops, allowing attendees to join via QR code.

DeepL says its voice-to-voice technology can learn and adapt to custom vocabulary, including industry-specific terms, as well as company and personal names.

Kutylowski noted that AI is reshaping customer service in the coming years. He pointed out that a translation layer helps companies provide support in languages where qualified staff are scarce and expensive to hire.

The company states that it controls the entire voice-to-voice stack. However, the current system converts speech to text, applies translation, and then converts the text back to speech. DeepL believes its years of work in text translation give it an edge in translation quality. Looking ahead, the company aims to develop an end-to-end voice translation model that bypasses the text step entirely.

DeepL faces competition from several well-funded startups working in related areas. Sanas, which raised $65 million last year from Quadrille Capital and Teleperformance, uses AI to modify a speaker's accent in real time—a tool primarily aimed at call center agents.

Dubai-based Camb.AI focuses on speech synthesis and translation for media and entertainment companies, including Amazon Web Services, helping them dub and localize video content at scale.

Palabra, backed by Reddit co-founder Alexis Ohanian's firm Seven Seven Six, is building a real-time speech translation engine designed to preserve both the meaning and the speaker's original voice, putting it in more direct competition with what DeepL is now building.