We often verbally express emotions in a multifaceted manner, they may vary in
their intensities and may be expressed not just as a single but as a mixture of
emotions. This wide spectrum of emotions is well-studied in the structural
model of emotions, which represents variety of emotions as derivative products
of primary emotions with varying degrees of intensity. In this paper, we
propose an emotional text-to-speech design to simulate a wider spectrum of
emotions grounded on the structural model. Our proposed design, Daisy-TTS,
incorporates a prosody encoder to learn emotionally-separable prosody embedding
as a proxy for emotion. This emotion representation allows the model to
simulate: (1) Primary emotions, as learned from the training samples, (2)
Secondary emotions, as a mixture of primary emotions, (3) Intensity-level, by
scaling the emotion embedding, and (4) Emotions polarity, by negating the
emotion embedding. Through a series of perceptual evaluations, Daisy-TTS
demonstrated overall higher emotional speech naturalness and emotion
perceiveability compared to the baseline.

在这篇论文中，我们提出了一种基于结构模型的情感文本转语音设计，旨在模拟更广泛的情感谱系。我们的设计 Daisy-TTS 中加入了韵律编码器，以学习具有情感可分离性的韵律嵌入作为情感的代理。通过一系列的感知评估，与基准相比，Daisy-TTS 展示了更高的情感语音自然度和情感可感知性。