DeepL, the German AI translation startup known for its high-quality text translations, hasentered the real-time voice translation arena with the launch of DeepL Voice. This new feature allows users to listen to someone speaking in one language and see anautomatic translation in another language, in real time.

DeepL Voice currently supports 13 languages for audio input, including English, German, Japanese, Korean, and Spanish. The translated captions are available for all 33 languages supported by DeepL Translator.

While DeepL Voice currently focuses on text-based translations for live conversations and video conferencing, the company hints at future audioand video output. Voice is where translation is going to play out in the next year, says Jarek Kutylowski, DeepL’s founder and CEO.

DeepL’s foray into real-time voice translation comes amidsta growing trend in the AI industry. Google has already incorporated real-time translated captions into its Meet video conferencing service, and several startups are developing voice translation services. Eleven Labs, for example, offers a dubbing service using AI-generated voices, while Panjaya utilizes deepfake technology to create translated videos withmatching audio.

Interestingly, there’s a symbiotic relationship between these companies. Panjaya uses Eleven Labs’ API, and Eleven Labs itself leverages DeepL’s translation technology. This interconnectedness highlights the collaborative nature of the AI landscape, where companies are building upon each other’s strengths to advance the field.

DeepL Voice is currently available as a standalone feature, but the company plans to offer an API in the future. This will allow developers to integrate DeepL’s voice translation capabilities into their own applications, further expanding the reach of this technology.

The launch of DeepL Voice marks a significant step forwardin the evolution of AI-powered translation. As the technology continues to develop, we can expect to see even more innovative and seamless ways to communicate across language barriers.

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