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English(EN) Self-EmoQ: Plutchik-Guided Value-based Planning to Drive Streaming Emotional TTS

AI框架实现流式情感语音合成

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一个新的对话式AI框架，使系统能够以流式文本到语音（TTS）的方式确定和表达情感。该方法使用一个即插即用的LLM模块，通过强化学习进行训练，并结合Plutchik的情感轮来指导情感输出。实验表明，该方法在情感确定和响应质量方面均优于传统的提示和微调技术，从而带来更具情感一致性和流畅性的用户体验。 AI

影响 通过实现更自然、更具上下文感知能力的情感表达，增强了对话式AI的语音合成能力。

排序理由 关于情感TTS新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI框架实现流式情感语音合成

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关于情感TTS新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yue Zhao, Hongyan Li, Yong Chen, Luo Ji ·

    Self-EmoQ：基于Plutchik的情感价值规划驱动流式情感TTS

    arXiv:2606.09837v1 Announce Type: cross Abstract: Emotional interaction is increasingly crucial for conversational AI, yet current systems lack a self-emotion determination mechanism to drive the streaming text-to-speech (TTS) synthesis. We propose an emotion-planning framework t…

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