Expressive speech synthesis aims to generate speech that captures a wide
range of para-linguistic features, including emotion and articulation, though
current research primarily emphasizes emotional aspects over the nuanced
articulatory features mastered by professional voice actors. Inspired by this,
we explore expressive speech synthesis through the lens of articulatory
phonetics. Specifically, we define a framework with three dimensions:
Glottalization, Tenseness, and Resonance (GTR), to guide the synthesis at the
voice production level. With this framework, we record a high-quality speech
dataset named GTR-Voice, featuring 20 Chinese sentences articulated by a
professional voice actor across 125 distinct GTR combinations. We verify the
framework and GTR annotations through automatic classification and listening
tests, and demonstrate precise controllability along the GTR dimensions on two
fine-tuned expressive TTS models. We open-source the dataset and TTS models.

通过声音的产生水平，我们以声韵学为基础，定义了一个由声门化、紧张度和共振三个维度构成的框架（GTR），来研究表达性语音合成，记录了一个包含 20 个中文句子以及 125 个不同 GTR 组合的高质量语音数据集（GTR-Voice），并通过自动分类和听力测试验证了该框架和 GTR 注释的精确可控性，并在两个经过微调的表达性 TTS 模型上展示了 GTR 维度上的精确控制能力，同时也开源了数据集和 TTS 模型。