The increasing adoption of text-to-speech technologies has led to a growing demand for natural and emotive voices that adapt to a conversation's context and emotional tone. This need is particularly relevant for interactive narrative-driven systems such as video games, TV shows, and graphic novels. To address this need, we present the Emotive Narrative Storytelling (EMNS) corpus, a dataset of high-quality British English speech with labelled utterances designed to enhance interactive experiences with dynamic and expressive language. We provide high-quality clean audio recordings and natural language description pairs with transcripts and user-reviewed and self-reported labels for features such as word emphasis, expressiveness, and emotion labels. EMNS improves on existing datasets by providing higher quality and clean recording to aid more natural and expressive speech synthesis techniques for interactive narrative-driven experiences. Additionally, we release our remote and scalable data collection system to the research community.

翻译：语音合成技术的日益普及催生了对能适应用户对话语境及情感基调的自然且富有情感声音的迫切需求，尤其在视频游戏、电视节目和图像小说等交互式叙事驱动系统中更为突出。为满足这一需求，我们提出情感叙事讲述（EMNS）语料库——一个带有标注语句的高质量英式英语语音数据集，旨在通过动态且富有表现力的语言增强交互体验。我们提供高质量纯净音频记录与自然语言描述配对数据，并附有转录文本以及用户评审与自我报告标注的特征标签，包括词语强调、表现力及情感类别。EMNS通过提供更高质量的纯净录音，改进了现有数据集，从而支持面向交互式叙事驱动体验的更自然且富有表现力的语音合成技术。此外，我们向研究社区发布我们开发的远程可扩展数据采集系统。