German Translation Firm DeepL Launches Aure Model to Preserve Tone and Emotion in Real-Time Translation
DeepL releases the Aure model, enabling real-time voice translation to carry over the original speaker's intonation, emotion, and speaking pace.
German translation technology company DeepL announced on November 11, 2026, the launch of a new voice model called Aure, designed to improve the naturalness of its real-time translation service, DeepL Voice. According to The Decoder, the model carries over tone, emotion, emphasis, and speaking pace from the original speaker's voice into the target language.
Previously, DeepL Voice generated translated speech from a static voice sample captured at the start of a conversation, meaning it could not pick up on mood shifts or sarcasm. Aure works differently by continuously analyzing both the translated text and the original audio as the conversation unfolds. During training, DeepL separates voice identity, speech melody, and content so each component can be transferred into the new language independently, using reinforcement learning to keep accents out of the output.
Aure runs automatically in DeepL Voice for Online Meetings, In-Person Conversations, and the DeepL API. At launch, the model supports English, German, Spanish, French, Italian, Japanese, Portuguese, and Korean. This follows DeepL's initial rollout of voice preservation features in September.