DeepL wants real-time translation to finally capture sarcasm and mood shifts

DeepL's new Aure model for DeepL Voice transfers tone, emotion, emphasis, and speaking pace from the original speaker into the target language by continuously analyzing both the translated text and original audio, unlike the earlier approach that used a static voice sample. Reinforcement learning keeps accents out of the output, and Aure runs automatically in DeepL Voice for Online Meetings, In-Person Conversations, and the DeepL API, launching with support for English, German, Spanish, French, Italian, Japanese, Portuguese, and Korean. The article also notes DeepL's earlier voice preservation rollout in September, its May restructuring that cut about 250 jobs, its acquisition of the Mixhalo team, and Block's Dessa speech model for detecting emotions and sarcasm.