DeepL 发布 Aure 语音模型，实时翻译可保留语气、语速和情绪
DeepL wants real-time translation to finally capture sarcasm and mood shifts
DeepL 推出新的 Aure 模型，能将说话者的语气、情绪、重音和语速延续到目标语言中，改变了此前依赖会话开始时静态语音样本、无法捕捉情绪变化和讽刺的方式。Aure 在对话过程中持续分析译文和原始音频，训练时将音色、语音旋律和内容分离以独立迁移，并通过强化学习去除口音，自动运行于 DeepL Voice 的在线会议、面对面对话和 DeepL API。
DeepL Voice's real-time translations are about to sound a lot more natural. The company's new Aure model carries over tone, emotion, emphasis, and speaking pace from the original speaker's voice into the target language. Until now, DeepL Voice generated translated speech from a static voice sample captured at the start of a conversation. That meant it couldn't pick up on mood shifts or sarcasm. Aure works differently, 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. Reinforcement learning keeps 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.
DeepL first rolled out voice preservation in September. In May, the company cut about 250 jobs to restructure around smaller, AI-powered teams as part of what it called becoming an "AI-native" company. DeepL also acquired the team behind audio streaming specialist Mixhalo to bolster its real-time speech translation. Block is chasing a similar goal of capturing meaning beyond words. The company recently unveiled Dessa, a speech model designed to detect emotions and sarcasm directly from audio.
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来源： The Decoder · the-decoder.com