DeepL, a prominent translation company renowned for its text-based tools, has today unveiled a comprehensive voice-to-voice translation suite. This new offering supports diverse applications, including business meetings, mobile and web-based conversations, and group discussions for frontline personnel via custom applications. Concurrently, the company is launching an API, enabling external developers and businesses to integrate DeepL's technology for specialized use cases, such as call center operations.
DeepL CEO Jarek Kutylowski explained the strategic pivot in an interview with TechCrunch, stating, "After spending so many years in text translation, voice was a natural step for us." He further elaborated, "We have come a long way when it comes to text translation and document translation. But we thought there wasn’t a great product for real-time voice translation." This move underscores the company's ambition to fill a perceived void in the market for high-quality, instantaneous voice translation.
Kutylowski highlighted the core challenge in developing a real-time translation product: achieving an optimal balance between minimizing latency – the delay from speech to translated audio playback – and ensuring the accuracy of the translated output.
DeepL is rolling out add-ons for popular platforms such as Zoom and Microsoft Teams. These integrations allow participants to either listen to real-time translated audio while others speak in their native languages or follow real-time translated text on screen. This program is currently in an early access phase, and organizations are invited to join a waitlist. Additionally, the company offers a product tailored for mobile and web-based conversations, facilitating both in-person and remote interactions.
The new suite also features a capability for group conversations in settings like training sessions or workshops, where participants can effortlessly join by scanning a QR code.
DeepL emphasized that its voice-to-voice technology possesses the ability to learn and adapt to customized vocabulary, including industry-specific terminology, company names, and personal names.
Kutylowski remarked on the transformative role of AI in shaping the future of customer service, suggesting that a robust translation layer empowers companies to deliver support in languages where skilled staff are often scarce and costly to employ.
The company asserts full control over its entire voice-to-voice technology stack. Currently, the system operates by converting speech to text, applying translation, and then converting it back to speech. DeepL believes its extensive background in text translation provides a distinct advantage in translation quality. Looking ahead, the company aims to develop an end-to-end voice translation model that bypasses the intermediate text conversion step entirely.
DeepL navigates a competitive landscape populated by several well-funded startups operating in related areas. Sanas, for instance, which secured $65 million last year from Quadrille Capital and Teleperformance, employs AI to modify a speaker’s accent in real time, primarily targeting call center agents.
Dubai-based Camb.AI specializes in speech synthesis and translation for media and entertainment entities, including Amazon Web Services, assisting them in dubbing and localizing video content at scale.
Palabra, backed by Reddit co-founder Alexis Ohanian’s firm Seven Seven Six, is developing a real-time speech translation engine designed to preserve both the meaning and the speaker’s original voice. This positions Palabra as a more direct competitor to DeepL's newly launched voice translation capabilities.
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